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UNRAVELING THE INFLUENCE OF FACTORS ON MICRO SMALL AND

MEDIUM-SIZED ENTERPRISES’ ADOPTION OF SOCIAL MEDIA

MARKETING AND ITS BUSINESS IMPACT

Steven Young

, J. Johny Natu Prihanto

, Prio Utomo

Faculty of Business, Universitas Multimedia Nusantara, Indonesia

1,2,3

steven.young@student.umn.ac.id

, johny.na[email protected]

, prio.utomo@umn.ac.id

ABSTRACT

The continuously growing opportunities in the digital economy have prompted the Indonesian

government to encourage Micro, Small, and Medium-sized Enterprises (MSMEs) to undergo digital

transformation. While there are various approaches available, marketing products/services through

social media is believed to be one of the most effective methods. To maximize the benefits of social

media marketing adoption for MSMEs, it is indeed crucial to identify the influential factors related to its

adoption. Therefore, this study aims to quantitatively identify the factors influencing social media

adoption among MSMEs in Indonesia. In this study, attention is directed toward five factors:

performance expectancy, social influence, effort expectancy, facilitating conditions, and operating costs.

The study incorporated 136 actively participating MSMEs that employed social media marketing. We

opted to employ Partial Least Squares Structural Equation Modeling (PLS-SEM) due to its suitability

for our sample size and potential data characteristics. As we were unsure about the normality of our data

and the presence of measurement issues, PLS-SEM provided a robust and flexible approach. It allows

us to analyze complex models and handle potential non-normal data and measurement concerns,

ensuring reliable results even if such issues arise. Data is processed using the SmartPLS 3.0 software.

The research findings indicate that the usage of social media marketing is influenced by performance

expectancy and social influence. However, factors such as effort expectancy, facilitating conditions, and

costs do not have a significant impact on social media adoption among MSMEs. Furthermore, the results

of the study highlight the positive impact of utilizing social media for marketing on the performance of

MSMEs, particularly in terms of increasing sales, enhancing customer relationships, improving

productivity, and fostering creativity. These findings suggest that MSMEs can leverage social media

platforms to achieve tangible benefits and enhance various aspects of their business operations.

Keywords: UTAUT; Micro, Small and Medium-sized Enterprises; Social Media Marketing

INTRODUCTION

The role of Micro, Small, and Medium Enterprises is crucial for the development of the

newly industrialized country’s economy. MSMEs play a central role in Indonesia's economy,

making substantial contributions to both the Gross Domestic Product (GDP) and employment

generation (Remmang et al., 2023; Sarfiah et al., 2019). The state minister for Cooperatives Small

and Medium Enterprises reports that approximately 99.9% of business entities in Indonesia

belong to the MSME category, amounting to around 64.2 million entities as of 2018. MSMEs

employ 117 million workers, comprising 97.0% of the total workforce in Indonesia's business

sector. MSMEs make up approximately 61.1% of the GDP, with the remaining 38.9% attributed

to large enterprises, showcasing their significant contribution to the national economy (Sangsoko,

2020).

The global outbreak of COVID-19 has necessitated swift adaptation to new environmental

conditions and behavioral patterns, commonly referred to as the "new normal." Consequently, the

integration of digital technology has become a fundamental element of everyday life,

encompassing MSMEs that have undergone business transformations (Dzul Fikry et al., 2023).

Amidst the pandemic, digital platforms have risen as the optimal solution, aiding MSMEs in

effectively carrying out their operations (Nelly, 2021). The survey results by McKinsey in March

2022 indicated a clear shift in consumer shopping behavior, transitioning from offline channels

(brick-and-mortar retail stores) to online channels across almost all product categories (Arora et

al., 2022).

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The  surge  in  internet  user  growth  in  Indonesia  creates  a  valuable  opening  for  digital 
MSMEs to enhance their market presence. Internet users in Indonesia have consistently increased 
over the past 5 years. By January 2022, it had reached 204.7 million users. This number accounts 
for 73.7% of the total national population, which is approximately 277.7 million people, and 
represents  a  54.3%  increase  compared  to  internet  users  in  2018  (We  Are  Social,  2022). 
Furthermore, Indonesia possesses significant potential for digital economic growth, positioning it 
as a prospective leader within the ASEAN region. In 2020, Indonesia achieved the highest digital 
economy  transaction  value  in  Southeast  Asia,  amounting  to  US$44  billion.  Future  forecasts 
suggest that by 2025, Indonesia's digital economy will soar to an estimated US$124 billion (Bain 
& Company et al., 2020). 
The growing adoption of social media in newly industrialized countries has emerged as a 
pivotal strategy for fostering the development of MSMEs. Social media has become one of the 
most popular choices as it facilitates rapid and transparent communication between two parties 
(such  as  businesses  and  customers),  empowering  businesses  to  proactively  understand  and 
effectively  address  customer  needs  (Qalati  et  al.,  2021).  Social  media  platforms  also  offer 
substantial potential for product sales. A survey conducted by We Are Social found that the search 
for  products  to  purchase  ranks  7th  among  the  reasons  why  individuals  use  social  media, 
accounting  for  25.3%  of  respondents  (We  Are  Social,  2023).  SMEs  can  capitalize  on  this 
opportunity, given that the survey highlights how 25% of social media users actively employ 
these platforms to explore and make purchases. 
However, data from the state minister for Cooperatives Small and Medium Enterprises in 
December  2022  indicates  a  low  number  of  businesses  that  have  undergone  digitalization  in 
Indonesia, with only 20.76 million out of a total of 64 million entities (Dewanto & Suyitno, 2023). 
The government is making concerted efforts to enhance digitalization among MSMEs, aiming to 
digitally onboard 30 million MSMEs by 2024 (Smesco & Kemenkopukm, 2021). As such, this study 
seeks to analyze the determinants that shape MSMEs' digital market share growth, with the aim 
of assisting stakeholders in devising policy strategies to expedite the achievement of the digital 
MSME target. 
 
RESEARCH METHOD 
Hypothesis 
There  have  been  several  previous  studies  to  gain  insight  into  the  factors  that  shape 
businesses' adoption of social media. Some of the theories that are often used, for example, TAM 
and UTAUT. Researchers use UTAUT because the theory was coined by (Venkatesh et al., 2012) 
as the addition and integration of several existing acceptance technology models. The variables in 
UTAUT can also explain the acceptance of technology with R2 reaching 69%, higher than previous 
theories (Venkatesh et al., 2012). The researcher also found several studies in other countries which 
provide insights into the elements influencing the utilization of social media marketing by MSMEs 
using the UTAUT theory.  
In research conducted by (Puriwat & Tripopsakul, 2021) in Thailand, individuals believe 
that a system can assist in their work to improve performance is the factor that most influences 
business people in using social media marketing. There are also several other studies where it 
appears that there is a notable and positive correlation between performance expectancy and the 
adoption of technology. (Chatterjee & Kumar Kar, 2020; Syaifullah et al., 2021) observed that 
business individuals tend to embrace social media for business marketing when they have a higher 
level of confidence in the positive impact it can have on their marketing efforts. In the midst of a 
pandemic, social media is also the optimal solution to help MSMEs in maintaining their business 
performance (Syaifullah et al., 2021). 
 Users will not hesitate to adopt a technology that can help if the use of the technology is 
easy (Kuo & Yen, 2009; Venkatesh et al., 2012). Compared to other online platforms, social media 
is a platform with the fewest efforts and applications that are quite familiar among business people, 
because  people are used to  using social media for  alternate functions  like communicating  or 
socializing with friends and family (Puriwat & Tripopsakul, 2021).   

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SI is defined as the level of interest someone has in social media perceived based on the 
beliefs and attitudes of others in using social media platforms (Sullivan & Koh, 2019). Previous 
research  by  (Abdat,  2020;  Jabeen  et  al.,  2022;  Puriwat  &  Tripopsakul,  2021),  described  the 
significant role of social influence in the acceptance and utilization of social media applications. 
The stronger the influence of the social environment on business stakeholders, the more it will 
shape their behavior in utilizing social media for business operations (Abbas et al., 2019; Puriwat 
& Tripopsakul, 2021). 
Previous studies have shown that the availability of affordable training facilities on social 
media marketing techniques for employees, supported by IT facilities such as internet network 
connectivity, and the support from all parties to create a conducive environment are motivating 
factors for the utilization of social media for marketing purposes (Chatterjee & Kumar Kar, 2020; 
Hung  &  Lai,  2015;  Schaar  et  al.,  2014).  MSMEs  would  readily  embrace  SMM  when  their 
employees have good training facilities and affordable internet facilities. If the facilities do not 
support it, then MSMEs will be resistant to the use of social media marketing (Syaifullah et al., 
2021). 
Numerous studies emphasize a connection between cost and the adoption of technology 
(Chatterjee & Kumar Kar, 2020; Chong & Chan, 2012; Syaifullah et al., 2021). Efforts to achieve 
cost efficiency aim to maintain stability and increase business competitiveness, especially because 
current  business  developments  continue  to  grow  rapidly,  resulting  in  increasingly  fierce 
competition (Febryanti et al., 2019). Price savings orientation is not only assessed in terms of 
savings,  but  can  also  be  seen  from  other  aspects,  such  as  not  incurring  additional  costs  for 
purchasing products or using services (Yeo et al., 2017). The role of cost is significant when it 
comes to the adoption of technology (Chong & Chan, 2012). MSME participants would refrain 
from utilizing social media marketing (SMM) if the associated costs are elevated. (Syaifullah et 
al., 2021). Their motivation to employ social media stems from the minimal entry barriers, cost-
effectiveness, and the absence of a necessity for advanced IT skills (Derham et al., 2011). SMM 
also allows businesses to gain cost savings in communicating and identifying consumer needs 
(Chatterjee & Kumar Kar, 2020). 
In Indonesia, approximately 167 million people are active users of social media, spending 
an average of 3 hours and 18 minutes per day on these platforms (Hassan et al., 2022; We Are 
Social, 2023). These statistics highlight the substantial market opportunity presented by social 
media,  as  it  has  emerged  as  a  convenient  platform  for  sharing  information  online  between 
companies and consumers, as well as among consumers worldwide, without any time limitations. 
The utilization of social media is particularly well-suited for MSMEs considering their limited 
resources, such as financial constraints and technical expertise (Fraccastoro et al., 2021; Rana et 
al.,  2019).  Marketing  on  social  media  can  enhance  trust  and  brand  loyalty  for  a  business. 
Furthermore,  social  media  marketing  facilitates  consumers  in  obtaining  information  about 
products  sold  by  companies  with  minimal  effort  (Agnihotri  et  al.,  2016;  Chung  &  Koo,  2015; 
Puspaningrum,  2020;  Zaglia,  2013).  Previous research  has  also  indicated a  positive  association 
between social media marketing and trust, closeness, and customer loyalty (Khoa, 2020; Li et al., 
2020). In addition, other studies found that the use of social media by companies brings about 
convenience in brand building and facilitates their business activities (Chatterjee & Kumar Kar, 
2020; Jibril et al., 2019; Sullivan & Koh, 2019).  The conceptual framework of this study is illustrated 
in Figure 2. 
 
   

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Figure 2.

SEM-PLS Result (Inner Model)

The hypotheses are as follows:

H1. PE has a positive and significant influence on SMEs' adoption of SMM

H2. EE has a positive and significant influence on SMEs' adoption of SMM

H3. SI has a positive and significant influence on SMEs' adoption of SMM

H4. FC has a positive and significant influence on SMEs' adoption of SMM

H5. The cost has a negative and significant influence on MSMEs’ adoption of SMM

H6. The utilization of Social Media Marketing (SMM) has a significant and positive impact on

the performance of MSMEs.

Research Design and Data Collection

The aim of this study was to explore the factors influencing the adoption of social media

marketing among micro, small, and medium enterprises (MSMEs), as well as its repercussions

on business outcomes. The objects of the research carried out are micro, small and medium

entrepreneurs who meet the criteria in (Undang-Undang (UU) Nomor 20 Tahun 2008 Tentang

Usaha Mikro, Kecil, Dan Menengah, 2008) and are active in using social media. The research

employed a quantitative approach, utilizing the partial least squares structural equation modeling

(PLS-SEM) technique to confirm the hypothesized relationships and authenticate the proposed

theoretical framework. The study's participants encompassed various micro, small, and medium

enterprises situated in Indonesia. The process of gathering data involved the distribution of an

online survey through popular social media platforms such as Facebook, Instagram, and

Whatsapp. According to (Hair et al., 2021), the inverse square root approach can be used in

determining the minimum number of samples. Assuming a general level of power of 80% and a

significance level of 5%, the minimum sample size (nmin) can be calculated using the formula:

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

















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nmin = numbers of minimum sample

pmin = path coefficient minimum

The minimum sample size can be calculated after the researcher collects data from

distributing questionnaires and performs an inner model analysis to acquire the lowest path

coefficient value among the variables that have a significant effect. In case there is an

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insufficiency of gathered data, the researcher will again increase the number of samples.

Researchers collected data for 3 weeks, and 136 samples were successfully collected. When the

data is processed, the smallest path coefficient value in this study is 0.369. By entering this value

into the formula above, the number 45.38 is obtained, so that the minimum number of samples in

this study has been fulfilled.

Questionnaire Development

Based on the indicators that have been developed, a pretesting process is carried out to

guarantee the non-redundancy, reliability, and suitability of the indicators used. In the final

questionnaire, there are 26 indicators used, which are presented in Table I. The questionnaire

consists of closed-ended questions, utilizing a 5-point Likert scale (ranging from 1 for Strongly

Disagree to 5 for Strongly Agree).

Table 1 Operational Variables

Construct

Items

Indicator

Performance

Expectancy

(PE)

PE1

Social media will be useful in running a business (Puriwat

& Tripopsakul, 2021)

PE2

Social media will increase your business profits (Puriwat &

Tripopsakul, 2021).

PE3

Social media can help you increase customer satisfaction

(Chatterjee & Kumar Kar, 2020).

PE 4

Social media will accelerate you in achieving business goals

(Puriwat & Tripopsakul, 2021).

Effort

Expectancy

(EE)

EE1

Social media will be easy for you to learn in running a

business (Puriwat & Tripopsakul, 2021).

EE2

Becoming skilled in utilizing social media for business

purposes can be achieved effortlessly (Puriwat &

Tripopsakul, 2021).

EE3

You can do sales transactions on social media quickly

(Puriwat & Tripopsakul, 2021).

EE4

You can easily advertise business products and services on

social media (Chatterjee & Kumar Kar, 2020).

Social Influence

(SI)

SI1

Individuals of significance recommend your engagement in

utilizing social media for business motives (Puriwat &

Tripopsakul, 2021).

SI2

Individuals who have an impact on your actions propose the

utilization of social media for business intentions (Puriwat

& Tripopsakul, 2021).

SI3

Individuals whose viewpoints you hold in high regard

propose your involvement in using social media for

business objectives (Puriwat & Tripopsakul, 2021).

SI4

People around you suggest that you use social media for

business purposes (Puriwat & Tripopsakul, 2021).

Facilitating

Condition (FC)

FC1

You possess the required knowledge to effectively employ

online social media for business endeavors (Puriwat &

Tripopsakul, 2021).

FC2

You possess connections who can provide assistance with

any social media challenges you might encounter (Puriwat

& Tripopsakul, 2021).

FC3

You have access to the necessary resources to effectively

utilize social media for business purposes (Puriwat &

Tripopsakul, 2021).

FC4

Social media seamlessly integrates with other platforms you

have employed (Puriwat & Tripopsakul, 2021).

Cost (COS)

COS1

The costs required to interact with customers will decrease

after using social media (Chatterjee & Kumar Kar, 2020).

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COS2

The expense related to discovering new customers will be

diminished by utilizing social media (Chatterjee & Kumar

Kar, 2020).

COS3

Social media will make the costs needed to increase brand

awareness cheaper (Chatterjee & Kumar Kar, 2020).

Social Media

Marketing

(SMM)

SM1

Marketing on social media is useful in advertising your

business products and services (Chatterjee & Kumar Kar,

2020).

SM2

You use social media as a marketing tool because your

competitors use it too (Chatterjee & Kumar Kar, 2020).

SM3

Employing social media marketing techniques contributes

to the enhancement of the business (Chatterjee & Kumar

Kar, 2020).

Impact on

Business (IOB)

IOB1

After engaging with social media, your customers

experience a heightened sense of connection to your

business (Chatterjee & Kumar Kar, 2020).

IOB2

Social media helps businesses in identifying customer needs

(Chatterjee & Kumar Kar, 2020).

IOB3

Your product sales have increased compared to before using

social media in business (Chatterjee & Kumar Kar, 2020).

IOB4

Marketing on social media helps in increasing the creativity

of the employees (Chatterjee & Kumar Kar, 2020).

RESULT AND DISCUSSION

Descriptive Statistics Result

The majority of respondents are MSME actors with the business category being in the type

of micro business and domiciled in Banten, DKI Jakarta, Bengkulu. All respondents have used

social media in marketing their business. A significant portion of participants are females

belonging to the age group of 25 to 42 years (millennial generation) and possess a bachelor's

degree. The demographic characteristics of the survey respondents are detailed in Table 2.

Table 2 Descriptive Statistics

Category

Small (Rp 300 M – Rp 2.5 B)

25.0

18.38%

Medium (Rp 2.5B – Rp 50 B)

22.0

16.18%

Micro (0 – Rp 300 M)

89.0

65.44%

Domicile

Banten

50.0

36.76%

Bengkulu

27.0

19.85%

DKI Jakarta

33.0

24.26%

Jawa Barat

13.0

9.56%

Others

6.0

4.41%

Sumatera Selatan

7.0

5.15%

Age

25 - 42 years

95.0

69.85%

43 - 57 years

23.0

16.91%

< 25 years

14.0

10.29%

> 57 years

4.0

2.94%

Last

Education

Associate Degree

6.0

4.41%

Bachelor

82.0

60.29%

15.0

11.03%

Senior High School

33.0

24.26%

Before testing the hypothesis, the researcher first measured the model (outer model) using

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SEM-PLS. Construct validity pertained to the degree of accuracy with which a collection of

observed variables authentically portrays the latent variables intended to be theoretically

measured. Criteria introduced by (Hair et al., 2017) were employed to assess convergent validity,

discriminant validity, and reliability. The results substantiated a combined count of 26 items

encompassing PE (four items), EE (four items), SI (four items), FC (four items), Cost (three

items), SMM (three items), and IOB (four items) meet the requirements of the validity and

reliability test. Every indicator displays item loadings exceeding 0.5, and the Average Variance

Extracted (AVE) value for each construct also surpasses the 0.5 threshold as proposed by (Hair

et al., 2017). Cronbach’s alpha coefficient for the instrument varies between 0.847 and 0.921,

while the composite reliability scores for the instrument fall within the range of 0.909 to 0.944.

The measurement model results are presented in both Table 3 and Table 4.

Table 3 Reliability and validity of constructs

Indicator

Convergent Validity

Internal Consistency Reliability

Loadings

AVE

Composite

Reliability

Cronbach's

Alpha

> 0,70

> 0,50

> 0.70

PE1

0,877

0,779

0,934

0,905

PE2

0,919

PE3

0,864

PE4

0,869

EE1

0,889

0,735

0,917

0,880

EE2

0,84

EE3

0,835

EE4

0,864

SI1

0,909

0,808

0,944

0,921

SI2

0,894

SI3

0,934

SI4

0,857

FC1

0,76

0,715

0,909

0,867

FC2

0,828

FC3

0,892

FC4

0,896

COS1

0,864

0,764

0,907

0,847

COS2

0,911

COS3

0,846

SMM1

0,805

0,793

0,919

0,868

SMM2

0,927

SMM3

0,933

IOB1

0,896

0,777

0,933

0,903

IOB2

0,916

IOB3

0,909

IOB4

0,799

The convergence validity indicators are standardized through Factor Loadings and the

Average Variance Extracted. All indicators achieved recommended values by (Hair et al., 2017)

represented convergent validity acceptance. To assess internal consistency reliability,

standardization is achieved through Composite Reliability (CR) and Cronbach's Alpha (Hair et

al., 2017). All constructs achieved recommended values by (Hair et al., 2017). Table 4 presents

the results of the discriminant validity test. Discriminant validity was successfully established as

evidenced by the fact that the value of the HTMT Confident Interval does not have a value of 1

(Hair et al., 2017).

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Table 4 Heterotrait-Monotrait Ratio (HTMT)

COS

IOB

COS

0,765

0,679

0,913

IOB

0,750

0,705

0,732

0,719

0,742

0,684

0,867

0,740

0,738

0,724

0,700

0,724

0,745

0,723

0,855

0,835

0,849

Structural Model and Hypotheses Testing

After the assessment of the measurement model, the subsequent phase involved the development

of the structural model (inner model). The outcomes of the proposed path model are depicted in

Figure 1, and the detailed results can be seen in Table 5.

Figure 1 SEM-PLS Result (Inner Model)

Table 5 Results of Hypothesis Testing

Effect

Path

Coefficient

p-value

Remarks

Effect on SMM

0,709

by PE

0,376

0,000 (*** p < 0,001)

Supported

by EE

0,048

0,309 (ns p > 0,05)

Not Supported

by SI

0,369

0.000 (*** p < 0,001)

Supported

by FC

0,080

0,191 (ns p > 0,05)

Not Supported

by COS

-0,088

0,125 (ns p > 0,05)

Not Supported

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Effect on IOB

0,589

by SM

0,767

0.000 (*** p < 0,001)

Supported

Seven constructs and twenty-six statement-based questions (items) were discerned.

Drawing upon the literature, a conceptual model was constructed, leading to the formulation of

six hypotheses. The conceptual model's validity was verified using PLS-SEM analysis. Following

the validation process, it became evident that among the six initially formulated hypotheses, three

hypotheses (H2, H4, H5) were not substantiated. This implies that the presumed impact of Effort

Expectancy (EE), Facilitating Conditions (FCO), and Cost (COS) on Social Media Marketing

(SMM) adoption has not been supported. Calculation of determinant coefficients (R2) indicates

that Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Facilitating

Conditions (FC), and Cost (COS) collectively account for 70.9% of the variability in Social Media

Marketing (SMM), as the corresponding coefficient of determination is 0.709 (R2). Among all

the independent variables (PE, EE, SI, FC, and COS), the impact of PE on SMM (H1) stands out

as the strongest, with a path coefficient of 0.376 and a high level of significance ***(P < 0.001).

On the other hand, the influence of EE on SMM (H2) is relatively modest, indicated by a path

coefficient of 0.048 and non-significant (ns) level of significance (p > 0.05). Furthermore, Social

Media Marketing (SMM) accounts for approximately 58.9% of the explanation of Impact on

Business (IOB) (H6), given the coefficient of determination (R2) of 0.589.

CONCLUSION

The characteristics of the respondents in this research survey are that the majority are

MSME actors with the business category being in the type of micro business and the majority are

domiciled in Banten, DKI Jakarta, Bengkulu, and have used social media to market their business.

The majority of respondents are also female, aged 25-42 years (millennial generation) with an

undergraduate degree. The use of social media as a marketing tool greatly influences the

development of MSME businesses. The results of the study show that the use of Social Media

Marketing in MSMEs will have an impact on business benefits, such as increasing product sales,

better relationships with consumers, ease in identifying customer needs, and increased employee

creativity. Expectations for increased performance have the strongest influence on MSME

behavior in adopting social media as a marketing tool. In addition, the opinions of people in the

social environment of MSME actors are quite influential on the behavior of MSMEs to use social

media as a marketing tool in running their businesses. As for the ease of use of marketing

techniques on social media, the condition of available facilities, and the cost savings factor, it has

not been proven to influence the behavior of MSMEs to adopt marketing on social media in

running their business. MSMEs in Indonesia still find it difficult to adopt social media marketing

in running their business. Some MSMEs cannot yet use social media marketing properly. Apart

from that, the available facilities, such as training and infrastructure, are still inadequate to

encourage MSMEs to adopt social media marketing. Improved facilities and effective training

will be able to help MSME players in adopting social media marketing in the future which will

have an impact on improving business performance.

In the research conducted, data dissemination was carried out using the researcher's social

media account, so that the number of respondents obtained was still not optimal. In addition, the

respondents obtained are also still in a scope that is too spread out. Further research can be done

by limiting certain regions/provinces to get an overview of an area. In addition, it is also possible

to modify the research model and add variables, such as adding variables from TAM theory, as

well as UTAUT2 or UTAUT 3, and the research model can be supplemented with moderating

variables such as age, level of education, gender and type of business category. In future studies,

it is recommended to further clarify and direct the criteria of respondents to the industry as well

as the requirements for activity on social media, for example, limiting the criteria of respondents

to a creative industry, or setting a minimum frequency of using social media, so that the selected

respondents are truly active in using the media social. In subsequent studies, the approach is still

Unraveling The Influence of Factors on Micro Small and Medium-Sized Enterprises’ Adoption of Social 
Media Marketing and Its Business Impact 
 
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using  a  single  cross-sectional  design,  where  the  number  of  samples  is  only  taken  once. 
Subsequent research can use a longitudinal design to get an overview of differences in business 
performance, before and after adopting social media marketing. 
REFERENCES 
Abbas, J., Mahmood, S., Ali, H., Raza, M. A., Ali, G., Aman, J., Bano, S., & Nurunnabi, M. 
(2019). The Effects of Corporate Social Responsibility Practices and Environmental Factors 
through  a  Moderating  Role  of  Social  Media  Marketing  on  Sustainable  Performance  of 
Firms’  Operating  in  Multan,  Pakistan.  Sustainability,  11(12),  3434. 
https://doi.org/10.3390/su11123434 Google Scholar 
Abdat, Fatmah Amir. (2020). Using UTAUT Model to Predict Social Media Adoption among 
Indonesian  SMEs.  Saudi  Journal  of  Economics  and  Finance,  4(10),  498–505. 
https://doi.org/10.36348/sjef.2020.v04i10.003 Google Scholar 
Agnihotri, R., Dingus, R., Hu, M. Y., & Krush, M. T. (2016). Social media: Influencing customer 
satisfaction  in  B2B  sales.  Industrial  Marketing  Management,  53,  172–180. 
https://doi.org/10.1016/j.indmarman.2015.09.003 Google Scholar 
Arora,  T.,  Jusi,  I.,  Adrian,  Kertawidjaja,  &  Potia,  A.  (2022).  Survey:  Indonesian  consumer 
sentiment  during  the  coronavirus  crisis.  https://www.mckinsey.com/capabilities/growth-
marketing-and-sales/our-insights/survey-indonesian-consumer-sentiment-during-the-
coronavirus-crisis#/ Google Scholar 
Bain & Company, Google, & Temasek. (2020). e-Conomy SEA 2020 Resilient and racing ahead: 
Southeast Asia at full velocity. Google Scholar 
Chatterjee, S., & Kumar Kar, A. (2020). Why do small and medium enterprises use social media 
marketing and what is the impact: Empirical insights from India. International Journal of 
Information  Management,  53.  https://doi.org/10.1016/j.ijinfomgt.2020.102103  Google 
Scholar 
Chong, A. Y.-L., & Chan, F. T. S. (2012). Structural equation modeling for multi-stage analysis 
on  Radio  Frequency  Identification (RFID)  diffusion in  the  health  care industry.  Expert 
Systems with Applications, 39(10), 8645–8654. https://doi.org/10.1016/j.eswa.2012.01.201 
Google Scholar 
Chung, N., & Koo, C. (2015). The use of social media in travel information search. Telematics 
and Informatics, 32(2), 215–229. https://doi.org/10.1016/j.tele.2014.08.005 Google Scholar 
Derham,  R.,  Cragg,  P.,  &  Morrish,  S.  (2011).  Creating  value:  An  SME  and  social  media. 
https://www.researchgate.net/publication/221229527 Google Scholar 
Dewanto, K., & Suyitno, H. (2023). Kemenkop UKM targetkan 24 juta UMKM masuk ekosistem 
digital pada 2023. https://www.antaranews.com/berita/3397599/kemenkop-ukm-targetkan-
24-juta-umkm-masuk-ekosistem-digital-pada-2023 Google Scholar 
Dzul Fikry, M., Sudanawati Rozas, I., & Muslihul Amin, F. (2023). Implementation of Business 
Process Reengineering To Minimize Customer Complaints. Return : Study of Management, 
Economic  and Bussines, 2(4), 367–388. https://doi.org/10.57096/return.v2i04.90 Google 
Scholar 
Febryanti,  A.  R.,  Koesdiningsih,  N.,  &  Rani,  A.  M.  (2019).  Prosiding  Manajemen 
Meminimumkan Biaya Produksi Menggunakan Perencanaan Agregat pada CV. Moonsoon 
Wear  Industries  Kota  Bandung  Minimize  Production  Cost  Using  Aggregate  Planning. 
Google Scholar 
Fraccastoro, S., Gabrielsson, M., & Pullins, E. B. (2021). The integrated use of social media, 
digital, and traditional communication tools in the B2B sales process of international SMEs. 
International  Business  Review,  30(4),  101776. 
https://doi.org/10.1016/j.ibusrev.2020.101776 Google Scholar 
Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial 
Least Squares Structural Equation Modeling (PLS-SEM) Using R. Springer International 
Publishing. https://doi.org/10.1007/978-3-030-80519-7 Google Scholar 

Unraveling The Influence of Factors on Micro Small and Medium-Sized Enterprises’ Adoption of Social 
Media Marketing and Its Business Impact 
 
1238                                       Return: Study of Management, Economic And Business, Vol 2 (12), December 2023 
 
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, Marko. (2017). A primer on partial least 
squares structural equation modeling (PLS-SEM). Google Scholar 
Hassan, H., Hsbollah, H. M., & Mohamad, R. (2022). Examining the interlink of social media 
use,  purchase  behavior,  and  mental  health.  Procedia  Computer  Science,  196,  85–92. 
https://doi.org/10.1016/j.procs.2021.11.076 Google Scholar 
Hung, Y.-H., & Lai, H.-Y. (2015). Effects of Facebook Like and Conflicting Aggregate Rating 
and Customer Comment on Purchase Intentions (pp. 193–200). https://doi.org/10.1007/978-
3-319-20678-3_19 Google Scholar 
Jabeen,  K.,  Suhail,  M.,  &  Ali,  A.  (2022).  Explaining  The  Influencing  Factors  Of  Cyber 
Entrepreneural  Behavior  On  Social  Media:  An  Implication  Of  Utaut  Model. 
https://Doi.Org/10.17605/Osf.Io/Mxnz7 Google Scholar 
Jibril, A. B., Kwarteng, M. A., Chovancova, M., & Pilik, M. (2019). The impact of social media 
on consumer-brand loyalty: A mediating role of online based-brand community. Cogent 
Business  &  Management,  6(1).  https://doi.org/10.1080/23311975.2019.1673640  Google 
Scholar 
Khoa, B. T. (2020). The Antecedents of Relationship Marketing and Customer Loyalty: A Case 
of the Designed Fashion Product. The Journal of Asian Finance, Economics and Business, 
7(2), 195–204. https://doi.org/10.13106/jafeb.2020.vol7.no2.195 Google Scholar 
Kuo, Y.-F., & Yen, S.-N. (2009). Towards an understanding of the behavioral intention to use 3G 
mobile  value-added  services.  Computers  in  Human  Behavior,  25(1),  103–110. 
https://doi.org/10.1016/j.chb.2008.07.007 Google Scholar 
Li,  M.-W.,  Teng,  H.-Y.,  &  Chen,  C.-Y.  (2020).  Unlocking  the  customer  engagement-brand 
loyalty relationship in tourism social media: The roles of brand attachment and customer 
trust.  Journal  of  Hospitality  and  Tourism  Management,  44,  184–192. 
https://doi.org/10.1016/j.jhtm.2020.06.015 Google Scholar 
Nelly, S. (2021). Digitalization as a Strategy for the Revitalization of Micro, Small and Medium 
Enterprises  (Msmes)  During  the  Covid-19  Pandemic  (Vol.  25).  http://annalsofrscb.ro 
Google Scholar 
Undang-undang (UU) Nomor 20 Tahun 2008 tentang Usaha Mikro, Kecil, dan Menengah, Pub. 
L. No. 93, Pemerintah Pusat (2008). Google Scholar 
Puriwat, W., & Tripopsakul, S. (2021). Explaining social media adoption for a business purpose: 
An  application  of  the  utaut  model.  Sustainability  (Switzerland),  13(4),  1–13. 
https://doi.org/10.3390/su13042082 Google Scholar 
Puspaningrum, A. (2020). Social Media Marketing and Brand Loyalty: The Role of Brand Trust. 
The  Journal  of  Asian  Finance,  Economics  and  Business,  7(12),  951–958. 
https://doi.org/10.13106/jafeb.2020.vol7.no12.951 Google Scholar 
Qalati, S. A., Yuan, L. W., Khan, M. A. S., & Anwar, F. (2021). A mediated model on the 
adoption of social media and SMEs’ performance in developing countries. Technology in 
Society, 64. https://doi.org/10.1016/j.techsoc.2020.101513 Google Scholar 
Rana, N. P., Barnard, D. J., Baabdullah, A. M. A., Rees, D., & Roderick, S. (2019). Exploring 
barriers of m-commerce adoption in SMEs in the UK: Developing a framework using ISM. 
International  Journal  of  Information  Management,  44,  141–153. 
https://doi.org/10.1016/j.ijinfomgt.2018.10.009 Google Scholar 
Remmang,  H.,  Baharuddin,  S.  M.,  Hasanuddin,  A.,  Hernita,  H.,  &  Hasanuddin,  A.  (2023). 
Empowerment  of  Micro,  Small,  and  Medium  Enterprises  in  South  Sulawesi  through 
Participatory  Economic  Transformation  (Case  Study:  Makass.  Ournal  of  Public 
Administration and Government, 5(3), 325–338. Google Scholar 
Sangsoko,  D.  (2020).  UMKM  Bangkit,  Ekonomi  Indonesia  Terungkit. 
https://www.djkn.kemenkeu.go.id/artikel/baca/13317/UMKM-Bangkit-Ekonomi-
Indonesia-Terungkit.html Google Scholar 
Sarfiah, S., Atmaja, H., & Verawati, D. (2019). UMKM Sebagai Pilar Membangun Ekonomi 
Bangsa.  Jurnal  REP  (Riset  Ekonomi  Pembangunan),  4(2),  1–189. 
https://doi.org/10.31002/rep.v4i2.1952 Google Scholar 

Unraveling The Influence of Factors on Micro Small and Medium-Sized Enterprises’ Adoption of Social 
Media Marketing and Its Business Impact 
 
1239 
Return: Study of Management, Economic And Business, Vol 2 (12), December 2023 
 
Schaar, A. K., Calero Valdez, A., Ziefle, M., Eraßme, D., Löcker, A.-K., & Jakobs, E.-M. (2014). 
Reasons for using social networks professionally: The influence of user diversity on usage 
motivation. Social Computing and Social Media: 6th International Conference, SCSM 2014, 
Held  as  Part  of  HCI  International  2014,  Heraklion,  Crete,  Greece,  June  22-27,  2014. 
Proceedings 6, 385–396. Google Scholar 
Smesco, & Kemenkopukm. (2021). 16,4 Juta UMKM Go Digital. https://smesco.go.id/berita/16-
koma-4-juta-umkm-go-digital Google Scholar 
Sullivan, Y. W., & Koh, C. E. (2019). Social media enablers and inhibitors: Understanding their 
relationships  in  a  social  networking  site  context.  International  Journal  of  Information 
Management, 49, 170–189. https://doi.org/10.1016/j.ijinfomgt.2019.03.014 Google Scholar 
Syaifullah, J., Syaifudin, M., Sukendar, M. U., & Junaedi, J. (2021). Social Media Marketing and 
Business  Performance  of  MSMEs  During  the  COVID-19  Pandemic.  Journal  of  Asian 
Finance,  Economics  and  Business,  8(2),  523–531. 
https://doi.org/10.13106/jafeb.2021.vol8.no2.0523 Google Scholar 
Venkatesh, Thong, & Xu. (2012). Consumer Acceptance and Use of Information Technology: 
Extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 36(1), 
157. https://doi.org/10.2307/41410412 Google Scholar 
We  Are  Social.  (2022).  Digital  2022  Indonesia.  https://datareportal.com/reports/digital-2022-
indonesia Google Scholar 
We  Are  Social.  (2023).  Digital  2023  Indonesia.  https://datareportal.com/reports/digital-2023-
indonesia Google Scholar 
Yeo, V. C. S., Goh, S.-K., & Rezaei, S. (2017). Consumer experiences, attitude and behavioral 
intention toward online food delivery (OFD) services. Journal of Retailing and Consumer 
Services, 35, 150–162. https://doi.org/10.1016/j.jretconser.2016.12.013 Google Scholar 
Zaglia, M. E. (2013). Brand communities embedded in social networks.  Journal of Business 
Research, 66(2), 216–223. https://doi.org/10.1016/j.jbusres.2012.07.015 Google Scholar 
  