Exploring Marketing Innovation on MSMEs in Indonesia:
A Descriptive Study
MARCELLA ASTRIANI1, MARIANI1, ANGELINE CLAIRINE1, MOHAMMAD ICHSAN1,
AGUNG SUDJATMOKO2
1Management Program, BINUS Business School, Bina Nusantara University,
Jakarta, INDONESIA
2Business Management Program, BINUS Business School, Bina Nusantara University,
Jakarta, INDONESIA
Abstract: - This research aims to describe the data by measuring the demographic survey of MSMEs in
Indonesia with innovation. This study also explicitly explores the interactions between demographic data
elements, especially gender with the most selected and used innovation in COVID-19 pandemic situation.
Utilizing cross-sectional survey data from 300 Indonesian MSMEs owners, this study is empirically tested
using descriptive analysis. Cross-tabulation is also used to examine demographic data elements, particularly
those related to gender and marketing innovation. The descriptive analysis frequency data shows that marketing
innovation has a greater impact on the performance of MSMEs during the COVID-19 pandemic than product
innovation,, process innovation and organizational innovation. Additionally, this study's cross-tabulation of
marketing innovation and gender shows that men tend to agree more on items MI2 and MI3 it’s because more
flexible and convenient in distributing products especially during COVID-19 pandemic crisis and women tend
to agree on MI1 it’s because women more active in social media than men. The findings show that
demography, especially in gender, has an influence on the tendency to use marketing innovation decisions in
COVID-19 pandemic situation. Therefore, the results of this study will increase our understanding of MSME
performance and innovation. It also creates an understanding for MSMEs owners of gender based MSME
enterprises in Indonesia.
Keywords: - cross-tabulation, COVID-19, descriptive analysis, gender, MSMEs, marketing innovation,
pandemic, performance.
Received: April 24, 2022. Revised: December 2, 2022. Accepted: December 22, 2022. Published: December 31, 2022
1 Introduction
In Indonesia, MSMEs are the business units with the
largest proportion. MSME itself is an abbreviation
of Micro, Small, and Medium Enterprises. MSMEs
control 99.9% of the business market in Indonesia
and generate a gross contribution of 60.51%. The
number of MSME units in Indonesia continues to
grow year by year. From 2010 to 2019, the growth
of MSMEs continued to grow. In 2010, the number
of MSMEs in Indonesia was around 52.8 million
units, and in 2019 the development of MSMEs
reached 65.5 million units, [1].
However, given the amount of data from the
Ministry of Cooperatives and Micro, Small, and
Medium Enterprises, MSMEs, which accounted for
99.9%, could only contribute 60.51% to GDP.
Meanwhile, the number of large Indonesian
companies, reaching only 0.01%, could contribute
39.49% to GDP, [2]. The data shows a huge
difference between MSMEs and large enterprises by
comparing Indonesia's percentage and GDP
contribution. Suppose seen and compared again
from the sales of UMKM PP number 7 of 2021
article 35 paragraph 3, [3], which shows that the
annual sales of micro-enterprises amount to two
billion rupiahs, small enterprises amounting to two
billion rupiahs to fifteen billion rupiahs and medium
enterprises amounting to fifteen billion rupiahs up to
fifty billion rupiahs. Micro enterprises, as seen from
sales, can only generate a maximum of 2 billion
rupiahs, while small and medium enterprises can
generate up to 2 billion rupiahs and more.
Therefore, a greater number of sales results will
contribute to greater GDP for Indonesia.
However, the number of micro-enterprises is
much larger than the number of small and medium
enterprises in Indonesia, [4]. Micro enterprises
account for 98.67% of the business share in
Indonesia. This puts the number of small and
medium enterprises far behind the number of micro-
enterprises. In addition, small enterprises, which
amounted to 1.22%, in percentage had a higher
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number than medium enterprises. Still, from the
contribution to GDP, it could only contribute 9.60%,
and medium enterprises with a smaller portion than
small enterprises could contribute 13.70%.
The COVID-19 pandemic has further
exacerbated the situation of MSMEs, and this
pandemic has caused turmoil in the economy. The
economic chaos causes the economic conditions to
suffer shocks, making the economy unstable, [2].
The economic turmoil also affects the growth and
development of MSMEs in Indonesia, [5].
According to the data by [6] 55.2% of MSMEs
experienced a decline in sales, 4.5% of MSMEs did
not experience growth, 36.7% of MSMEs did not
achieve sales during the pandemic, and only a tiny
proportion of MSMEs whose sales increased during
the pandemic, namely by 3.6%. From the data, some
MSMEs have grown but compared to the data, more
MSMEs have experienced a decline in sales
compared to MSMEs that have experienced an
increase in sales. This is because, during the
COVID-19 pandemic, the government had to make
a large-scale social restriction policy (PSBB). With
this PSBB, there is an 84.20% decrease in income
for MSMEs in Indonesia, [7].
A survey by Bank Indonesia indicated that the
performance of MSMEs had experienced a sharp
decline due to the outbreak of COVID-19, [8].
During the pandemic, the performance of MSMEs
deteriorated and MSME credit data during the
pandemic showed that MSME growth experienced
negative growth of minus 1.18%. The growth
recorded in 2021 compared to credit growth before
the COVID-19 pandemic was insignificant, only
0.4%, [9]. With this pandemic, it is also difficult to
obtain the raw materials used to manufacture goods,
and a change in people's behavior when shopping
leads to a drop in income, [10].
Previous research from [11] found that in a
situation like the COVID-19 crisis, a company or
organization can be freed from the COVID-19 crisis
by innovating because innovation is a driving factor
in achieving success. So, it can be concluded that
innovation is one of the critical factors to be
considered for MSMEs in COVID-19 pandemic
situation. From those data and statement, we want to
explore more about the demographic condition and
MSMEs innovation practices especially in
Indonesia. Therefore, this research aims to describe
the data by measuring the demographic survey of
MSMEs in Indonesia with innovation. This study
also explicitly explores the interactions between
demographic data elements, especially gender with
the most selected and used innovation in COVID-19
pandemic situation.
2 Literature Review
2.1 COVID-19
Many MSMEs fail and experience no growth due to
pre-existing issues such as little or no improvement
in market knowledge, lack of technical and business
management skills, lack of formal planning and
demand forecasting, and limited resources.
Therefore, this makes MSMEs very vulnerable to
events that occur within the internal and external
framework of MSMEs, [12]. The outbreak of
COVID-19 has a tremendous impact on global
society and the global economy. All activities in the
worldwide community are disrupted and altered,
including the global economy, which has undergone
drastic changes, [13].
COVID-19 has reduced the population's
purchasing power, which impacts business income,
[14]. Due to the COVID-19 shock, the government
has come together to create an emergency response
that includes measures to contain the pandemic and
economic policies, [15]. In the research [16], it was
revealed that government action against COVID-19
was carried out by establishing social restrictions or
quarantine regulations where the public was asked
to reduce social activities that involved many
people. This social restriction has proven effective
in reducing the spread of COVID-19. The research
by [17] found that the social restrictions caused by
COVID-19 have a negative impact on performance.
It is because there is a reduction in sales volume that
makes small and medium enterprises experience
cash flow difficulties that impact business
operations, [18]. MSMEs are also one of the sectors
hit hardest by the impact of COVID-19 pandemic,
[19]. Several studies have been conducted for this
COVID-19 variable, for example, in research by
[20] that examines the impact of COVID-19 on
startups. The study by [21] also uses COVID-19 as a
search variable that affects performance.
2.2 Innovation
Innovation is defined as realizing new original ideas
throughout the organization to introduce new
products to the market through a combination of
strategic direction and innovative behavior so that
this innovation can create value for customers by
implementing new methods, [22]. According to
Schumpeter's theory, innovation is divided into five
types: introducing new products, new production
methods, opening new markets, developing new
sources of supply, and new industrial structures,
[23]. The innovation theory used to explain growth
through change must be initiated and complemented
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by the RBV (Resource Base View) theory. The
RBV (Resource Based View) theory emphasizes the
importance of the company's resources. RBV
(Resource Based View) theory is the application of
unique capabilities and resources that are valuable,
cannot be perfectly imitated, and cannot be replaced
by the business that leads to better innovation that
improves business performance, [24].
Innovation is crucial for sustainable development
and competitiveness and can increase business
profits, [25]. Micro, small and medium-sized
enterprises (MSMEs) have limited resources, so
they must look for more efficient ways, especially
concerning COVID-19. MSMEs need to innovate
and improve their offerings of goods, products, and
services to meet changing market needs. Innovation
has become a means that allows an MSME to
transform and continue to grow to survive in the
market using all available resources in the
organization, people, technology, and finance, [26].
Innovation is divided into the application of
significantly improved new products (goods or
services), process, new marketing methods, and new
organizational forms in business practices,
workplace organization, and external relations, [27].
Product innovation is defined as a development
aimed at improving the quality of a product or
service that differs from the previous. Product
innovations are classified as new innovations to the
market or the company, [28]. Product innovation is
also essential for the growth and sustainability of
SMEs, [29]. Product innovation has three indicators:
increasing the number of products, expanding new
markets by developing new products, [30], [31], and
launching products in line with market demand,
[30], [32].
Process innovation is the introduction of new
methods or ways that change how a business
operates. Process innovation involves critical
engineering, equipment, and software changes that
adapt to processes and increase the efficiency of a
company's production or service delivery systems,
[33]. Process innovation can enable SMEs to cost-
effectively improve the life cycle of product
development, production, and delivery of goods,
[29]. Process innovation has four indicators such as
an increase in implementation of the production
process, [34], [31], a reduction in variable costs,
[34], [35], in the process production uses advanced
technology, [30], [31], and uses new processes and
methods, [36].
Organizational innovation is the application of
significantly new organizational methods in
business practices, workplace organizations, or
external relations of an institutional unit. These
innovations can lead to significant changes in
organizational structures, work environments, and
new forms of management, [33]. The indicators of
organizational innovation are new business
practices, new knowledge management systems, the
development of new ways of engaging with
research-based customers, [34], [37], distribution of
responsibilities and decision-making, [34] and
updating the organizational structure, [34], [38].
Marketing innovation uses new marketing methods,
changing product design, placement, and promotion,
[34]. Marketing innovation focuses on customer
needs and involves new markets that aim to increase
company sales, [28]. Marketing innovation has
several indicators, including new media or
techniques (MI1), new sales channels or placements
from research (MI2), [34], and using new research-
based distribution channels (MI3), [31], [34], [35].
Several studies have examined this dimension of
innovation, such as research by [39] examining
product and process innovation. The study by [35]
addresses the four dimensions of innovation
conducted on Lebanese SMEs. This study revealed
that marketing innovation, product innovation,
process innovation, and organizational innovation
have a positive impact on performance. This is also
shown by [31] research which reveals the significant
contribution of product, process, marketing, and
organizational innovation dimensions to
performance.
2.3 MSME Performance
The performance of an organization can be defined
as the ability of the organization to achieve its
objectives by using resources effectively and
efficiently, [40]. According to [41] performance is
defined as the contribution made by an entity
through its actions to the achievement of objectives
and the fullest satisfaction of the wants and needs of
key stakeholders. Performance is generally
measured in financial and non-financial terms.
Performance in the form of finance is the growth in
sales, enterprise value, and earnings, such as return
on investment and assets, stock market index, and
liability ratio, [33]. In contrast, performance in non-
financial forms is social responsibility,
organizational survival, quality services, targeting
and outreach, products and services, and member
benefits, [42].
Performance is closely linked to a company's
competitive advantage, core competencies, and
innovation capabilities. This is also in line with the
opinion expressed in [43] who revealed that
companies with sources of competitive advantages
in a changing global market are more likely to
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survive and achieve superior performance. To
improve a company's performance and survival,
innovation is necessary. In the research by [44] it
was found that there is a positive and significant
relationship between innovation and performance,
and the study by [45] also found that innovation
makes an excellent contribution to performance.
3 Research Methodology
3.1 Sample and data source
This research is based on a qualitative approach to
describe the data of demographic of MSMEs in
Indonesia with innovation. We use a descriptive
analysis method. The results of the descriptive
research are presented in the form of tables or
graphs and descriptions of the data results, [46]. The
unit of analysis used in this study is the
organization, namely MSMEs in Indonesia. With
business owners as representatives of an MSME
unit. The time horizon is cross-sectional because the
data collection is carried out over time, [47]. The
population of this study consists of MSMEs in
Indonesia, whose total number is not known in
certainty.
The method used in this study is a non-
probability sampling method in which the exact
number of populations in the data collection or the
sample is unknown, with a sampling technique
using convenience sampling where the sample is
obtained from a population willing to provide
information, [48]. The number of samples taken
using Hair's formula, where the number of each item
owned in the study is multiplied by 10, [49].
Research data was collected using a cross-sectional
approach for one month by distributing research
questionnaires with the help of a third party. The
questionnaire is divided into two parts consisting of
demographic data, including age, gender, education,
province, and type of business, as well as statements
on study variables composed of 23 statements to
owners of MSMEs in Indonesia. Respondents'
responses to the research statements used a Likert
scale ranging from 1 (strongly disagree) to 5
(strongly agree).
The data obtained from the survey results are
divided into demographic data which will be
analyzed by descriptive analysis with nominal data
and innovation variable data which will be analyzed
by descriptive analysis with ordinal data. Statistical
analysis was carried out using SPSS (Statistical
Product and Service Solution) software and for
demographic data a basic statistical analysis was
carried out to find the frequency value while the
innovation variable data included product, process,
marketing and organizational innovation by looking
for the mean, median, mode, standard deviation,
variance, skewness, kurtosis, range, minimum, and
maximum. In addition to analyzing individual
attributes, this study explicitly explores the
interaction between demographic data elements,
especially gender, and marketing innovation using
cross-tabulation data analysis.
4 Results
4.1 Data demography
This study’s results descriptively revealed the
respondents’ characteristics along several
dimensions, namely gender, province, age,
education, and type of business. In this study, 300
MSME owner respondents were collected from the
beginning of July 2022 to the end of July 2022. The
characteristics of this study's respondents are
presented in Table 1.
Table 1. Indonesian MSME demographic survey
data
Frequency
(%)
Gender
Woman
61.7%
Men
38.3%
Province
West Java
25.7%
Special Region of Jakarta
16.3%
East Java
13.3%
Other
13.0%
Central Java
09.70%
Banten
08.30%
North Sumatra
06.00%
Yogyakarta
04.30%
South Sulawesi
03.30%
Age Group
17 - 25 Years old
44.00%
25 - 33 Years old
32.30%
33 - 41 Years old
14.7%
Other
00.09%
Education
Senior High School or
Vocational High School
47.70%
Bachelor (S1)
38.00%
Diploma (D1/D2/D3)
09.70%
Other
5%
Type of business
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Accommodation Provider and
Food & Drink Provider
108
36%
Wholesale and Retail
94
31.30%
Activities that have no clear
boundaries
42
14.00%
Transportation, Warehousing,
and Communication
23
7.70%
Education Services
19
6.3%
Other
14
5%
According to the data, the female survey
respondents consisted of 185 respondents, and the
male respondents consisted of 115 respondents out
of a total of 300 respondents received. From the 300
MSMEs data collected from 19 provinces of
Indonesia, West Java has the highest number of
respondents with 77 respondents, followed by the
Special Capital Region of Jakarta, which has the
second highest number of respondents with 49
respondents, and East Java has the third highest
number of respondents with 40 respondents, Central
Java with 29 respondents, Banten with 25
respondents, North Sumatra with 18 respondents,
Yogyakarta with 13 respondents, South Sulawesi
with 10 respondents. And because the number of
respondents from some of the provinces is low, the
author decided to combine the following provinces
into "Other" categories, including the province of
Bali and South Kalimantan with six respondents,
Lampung, West Sumatra, and Riau with five
respondents, South Sumatra, Aceh, and East
Kalimantan with three respondents, West Papua,
North Sulawesi, and Bangka Belitung Island with
one respondent.
From the results of the survey, MSME owners
are divided into several age groups. The 17-25 age
group has the highest number of 132 respondents,
the 25-33 age group with a total of 97 respondents,
and the 33-41 age group with a total of 44
respondents. Because the number of respondents in
some age groups is small and less significant, the
authors decided to combine these two age groups
into another category which is composed of an age
group > 41 years with a total of 21 respondents and
from an age group < 17 years with a total of 6
respondents. From the survey results of the
education background, MSME business owners at
most have an educational background with senior
high school or vocational high school education
levels, with a total of 143 respondents. They are
followed by a bachelor's degree (S1) from 114
respondents and a diploma degree (D1/D2/D3) from
29 respondents. Some of the numbers of
respondents are also low and insignificant;
therefore, the authors decided to group these
different levels of education into another category
consisting of master's degree (S2) with 9
respondents, junior high school with 4 respondents,
and primary school with 1 respondent.
From the survey, the business types are divided
into 10 categories consisting of business type
categories that accommodation provider and food
services with 108 respondents, wholesale and retail
trade with 94 respondents, activities that have no
clear boundaries with 42 respondents,
transportation, warehousing, and communication
with 23 respondents, educational services with 19
respondents. Because the number of respondents
from this type of business is small and less critical,
the authors decided to group several of these
businesses into "Other" categories composed of
agricultural, hunting, and forestry business types
with 8 respondents, individual services serving
households with 2 respondents, community services,
social culture, entertainment, and other individuals
with 2 respondents, and construction and financial
intermediaries, each with 1 respondent.
4.2 Descriptive Analysis of Variable
Before proceeding with cross-tabulation data
analysis, performing a descriptive analysis of the
data using SPSS software is essential. Our analysis
is presented in Table 1, and Table 2. It is worth
mentioning that descriptive analysis of innovation
variables includes the product, process, marketing,
and organizational innovation.
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Table 2. Analysis variable with descriptive statistics
Mean
Median
Modus
Std.
Deviation
Variance
Skewness
Kurtosis
Range
Minimum
Maximum
Product
Innovation
(PT)
3.307
3.000
3.000
1.094
1.197
-0.293
-0.435
4.000
1.000
5.000
Process
Innovation
(PS)
3.490
3.000
3.000
0.993
0.987
-0.281
-0.207
4.000
1.000
5.000
Marketing
Innovation
(MI)
3.763
4.000
5.000
1.243
1.546
-0.720
-0.520
4.000
1.000
5.000
Organizational
Innovation
(OI)
3.480
4.000
4.000
1.029
1.060
-0.400
-0.221
4.000
1.000
5.000
Considering the mean or mean value of the variable
value distribution, Marketing innovation has the
highest value, which is 3.763, compared to product
innovation which has a value of 3.307, process
innovation has a value of 3.490, and organizational
innovation has a value of 3.480. The median value
of marketing innovation and organizational
innovation is 4, which is higher than product
innovation and process innovation, which have a
value of 3. The marketing innovation mode has a
value of 5, which is higher than product innovation,
process innovation which has a value of 3, and
organizational innovation, which has a value of 4.
Followed by another descriptive statistic value,
product innovation has a standard deviation of
1.094, a variance of 1.197, a skewness of -0.293,
and a kurtosis of -0.435. The process innovation has
a standard deviation of 0.993, a variance of 0.987, a
skewness of -0.281, and a kurtosis of -0.207.
Marketing innovation has a standard deviation of
1.243, a variance of 1.546, a skewness of -0.720,
and a kurtosis of -0.520. Organizational innovation
has a standard deviation of 1.029, a variance of
1.060, a skewness of -0.400, and a kurtosis of -
0.221. And all the innovation has a range of 4.000, a
minimum of 1.000, and a maximum of 5.000. From
this data, we can conclude that marketing innovation
has the highest score than of innovations, so we
choose this innovation for the next cross tabulation
analysis.
4.3 Cross Tabulation Analysis
In addition to analyzing individual attributes, this
study explicitly explores the interactions between
demographic data elements, especially gender, with
marketing innovation. From the descriptive analysis
frequency data, as shown in Table 3, and Table 4,
marketing innovation has more impact during the
COVID-19 pandemic to help the performance of
MSMEs.
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Table 3. Cross tabulation of MI1 and gender
MI1
Total
1.00
2.00
3.00
4.00
5.00
Gender
Men
Count
13
7
21
23
51
115
Expected count
11.1
4.2
19.6
24.2
56.0
115.0
% Within Gender
11.3%
6.1%
18.3%
20.0%
44.3%
100.0%
% Within MI1
44.8%
63.6%
41.2%
36.5%
34.9%
38.3%
% Of Total
5.3%
1.3%
10.0%
13.3%
31.7%
61.7%
Women
Count
16
4
30
40
95
185
Expected count
17.9
6.8
31.5
38.9
90.0
185.0
% Within Gender
8.6%
2.2%
16.2%
21.6%
51.4%
100.0%
% Within MI1
55.2%
36.4%
58.8%
63.5%
65.1%
61.7%
% Of Total
5.3%
1.3%
10.0%
13.3%
31.7%
61.7%
Total
Count
29
11
51
63
146
300
Expected count
29.0
11.0
51.0
63.0
146.0
300.0
% Within Gender
9.7%
3.7%
17.0%
21.0%
48.7%
100.0%
% Within MI1
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
% Of Total
9.7%
3.7%
17.0%
21.0%
48.7%
100.0%
Table 4. Cross tabulation of MI2 and gender
MI2
Total
1.00
2.00
3.00
4.00
5.00
Gender
Men
Count
18
9
17
21
50
115
Expected count
18.0
6.5
19.6
21.1.
49.8
115.0
% Within Gender
15.7%
7.8%
14.8%
18.3%
43.5%
100.0%
% Within MI2
38.3%
52.9%
33.3%
38.2%
38.5%
38.3%
% Of Total
6.0%
3.0%
5.7%
7.0%
16.7%
38.3%
Women
Count
29
8
34
34
80
185
Expected count
29.0
10.5
31.5
33.9
80.2
185.0
% Within Gender
15.7%
4.3%
18.4%
18.4%
43.2%
100.0%
% Within MI2
61.7%
47.1%
66.7%
61.8%
61.5%
61.7%
% Of Total
9.7%
2.7%
11.3%
11.3%
26.7%
61.7%
Total
Count
47
17
51
55
130
300
Expected count
47.0
17.0
51.0
55.0
130.0
300.0
% Within Gender
15.7%
5.7%
17.0%
18.3%
43.3%
100.0%
% Within MI2
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
% Of Total
15.7%
5.7%
17.0%
18.3%
43.3%
100.0%
Table 5. Cross tabulation of MI3 and gender
MI3
Total
1.00
2.00
3.00
4.00
5.00
Gender
Men
Count
13
9
23
26
44
115
Expected count
13.8
8.8
22.2
29.9
40.3
115.0
% Within Gender
11.3%
7.8%
20.0%
22.6%
38.3%
100.0%
% Within MI3
36.1%
39.1%
39.7%
33.3%
41.9%
38.3%
% Of Total
4.3%
3.0%
7.7%
8.7%
14.7%
38.3%
Women
Count
23
14
35
52
61
185
Expected count
22.2
14.2
35.8
48.1
64.8
185.0
% Within Gender
12.4%
7.6%
18.9%
28.1%
33.0%
100.0%
% Within MI3
63.9%
60.9%
60.3%
66.7%
58.1%
61.7%
% Of Total
7.7%
4.7%
11.7%
17.3%
20.3%
61.7%
Total
Count
36
23
58
78
105
300
Expected count
36.0
23.0
58.0
78.0
105.0
300.0
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Marcella Astriani, Mariani, Angeline Clairine,
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% Within Gender
12.0%
7.7%
19.3%
26%
35%
100.0%
% Within MI3
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
% Of Total
12.0%
7.7%
19.3%
26%
35%
100.0%
4.3.1 Cross Tabulation of Marketing Innovation
and Gender
As seen from marketing innovation, the MI1 item
deals with the use of social media in marketing
which is crosstab to gender. 51.4% of women
respondents strongly agreed with item MI1. In
contrast, 44.3% of men respondents strongly agreed
with item MI1. Our findings are presented in Table
5. When comparing women and men respondents, it
can be concluded that this MI1 item received a more
excellent positive response from women than men.
The marketing innovation shows that the MI2 item
deals with sales in marketplaces like Shopee, Gojek,
Tokopedia, et cetera, which is crosstab to gender.
43.2% of women respondents strongly agreed with
MI2. In contrast, 43.5% of men respondents
strongly agreed with MI2. This MI2 item contrasts
with the MI1 item, and, when compared to women
and men respondents, it can be concluded that MI2
received a more excellent positive response from
men than women. However, the percentage
difference between each gender was only 0.3%. As
seen from MI3 regarding the use of delivery
services to distribute products which is crosstab
with gender. 33% of women strongly agreed with
MI3. On the other hand, 38.3% of the men also
answered strongly agreed with MI3. The difference
in percentage between men and women in this item
is noticeable, with a difference of 5.3%. Of course,
this item seems to have the most apparent difference
of opinion between men and women. It can be
concluded that the MI3 item received a more
excellent positive response from men than women.
5 Discussion
5.1 Demographic Analysis
Java island is one of Indonesia's most populated
areas, with a total of 151.6 million inhabitants, [50].
This makes the number of MSMEs in Java very
high compared to other regions. The survey data
shows that the top 3 provinces with the most
MSMEs surveyed are in Java, including West Java,
the Special Region of Jakarta, and East Java. Many
MSMEs are located in Java because Java is the
center of economic activity in Indonesia. Much of
the development in Indonesia is carried out on Java
Island, and the center of government or the capital
of Indonesia is also located on Java Island, [51].
From these data, it can be concluded that there is
more women respondent than men respondent.
MSME actors in Indonesia comprise of 61.7%
women and 38.3% men, resulting in more women
becoming entrepreneurs than men, [52]. Another
reason MSME actors are women is that women
entrepreneurs are more likely to employ women and
provide motivational support to other women to
start their businesses, [53]. During the G20 event,
President Jokowi, the President of Indonesia, also
discussed the role of women in developing MSMEs
in Indonesia. Furthermore, President Jokowi also
strongly supports women in the MSME sector, [52].
According to these data, many Indonesian
MSMEs are engaged in accommodation, food and
drink providers, and wholesale and retail are the
most common and largest type of MSME business.
This is evident from [54] data which shows that
these two types of businesses have the highest
number. Business players prefer to work in the food
and beverage industry because food is everyone's
need, and the food and beverage industry has a
broad target market, [55]. Moreover, wholesalers
and retailers are more convenient in their business
processes as they do not require changing the
product's shape. Another interesting thing here is
construction, MSMEs have now entered a broader
realm of business types, and although the numbers
are not too big, it's a good development for MSMEs
because the types of businesses are becoming more
diverse and broader. The government also supports
this by involving MSMEs in the existing projects so
that types of business in MSMEs like construction
can grow faster and the economic turnover of
MSMEs also accelerates, [56].
From this, we can learn about the demographic
condition of MSMEs in Indonesia, especially during
the COVID-19 pandemic condition. We also can
learn more about provinces that have many MSMEs,
the gender background of MSMEs owners, the
educational background, the age range of MSMEs
owners, and the type of business. As a result,
business owners can use this study to make business
judgments before they decide to build or develop
their business. This study also can help the
government to know more about the condition of
MSMEs in Indonesia.
5.2 Descriptive Analysis of Variable
From the comparison of the descriptive analysis
data on the frequency of mean, median, and mode of
each innovation variable, the mean value indicates
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that MSMEs in Indonesia agree more that marketing
innovation has an impact on MSME performance
during the COVID-19 pandemic, as its mean value
is 3.763, which is higher than other innovations.
Median value data shows that Indonesian MSMEs
are more in agreement with marketing innovation
and organizational innovation to impact MSME
performance during the COVID-19 pandemic
because, from the median value sorted, it can be
seen that these two innovations have the same
number, which is 4. From the mode data, it can be
seen that MSMEs in Indonesia strongly agree with
marketing innovation to impact MSME performance
during the pandemic of COVID-19 because the
mode of marketing innovation shows a value of 5.
So, it can be concluded from the frequency values of
the mean, median, and mode indicate that
Indonesian MSMEs are more in agreement with
marketing innovation in impacting MSMEs’
performance during the COVID-19 pandemic.
Apart from the marketing innovation that got the
most votes for the impact on MSMEs in Indonesia
during COVID-19, if we look at the average
number, product innovation placed second after
marketing innovation, which is 3.490.
Organizational innovation is in third place, with
3.480 and the last is process innovation with 3.397.
It can be concluded that product innovation,
organizational innovation, and process innovation
also bring an impact on MSME performance in
Indonesia, although not as big as marketing
innovation. From this, we also conclude that
business owners in Indonesia already used
innovation for their business especially marketing
innovation. Therefore, business owners also can
consider using marketing innovation in their
businesses, especially business owners in Indonesia
because it has more impact on their business when
facing the COVID-19 pandemic situation.
5.3 Cross-tabulation Analysis of Marketing
Innovation and Gender
From demographic and innovation descriptive
analysis, we can understand the state of MSMEs in
Indonesia in more detail starting from gender,
province, age range, education, and type of business
with preferences for the types of innovations
implemented by MSMEs in Indonesia. Business
owners also can understand which types of
innovations are suitable to influence their business
performance in the conditions of the COVID-19
pandemic. In order to see in more detail decision-
making and innovation preferences, especially
marketing innovations with gender demographics, a
crosstabulation analysis was carried out.
Item MI1 shows that women are more active and
prefer to use social media in their business than
men, [57]. This is in line with data, that show
Indonesian women tend to be more active in using
social media than men. Item MI2 data analysis item
results, the difference between women and men is
not too large. It can be a positive sign for MSMEs
because there is increasing digitalization support in
Indonesia, especially on the issue of gender
equality, as most MSME owners are women.
Through its various work programs, the government
continues to strive to increase the knowledge of
Indonesian women on information technology and
digitalization, [58]. The results of this survey can
also show that MSMEs in Indonesia, in terms of
digital knowledge and information technology, are
no longer concerned with gender, or it can be
concluded that gender equality in MSMEs in
Indonesia has increased.
However, item MI3 is the item that is mostly
dominated by a positive response from men. In
business, men relatively choose to use delivery
services than women. From this, it can be seen that
gender differences affect different choices or
preferences for marketing innovations. So that it can
be interpreted that gender has an influence on the
tendency to make marketing innovation decisions in
the COVID-19 pandemic situation.
6 Conclusion
In this study, it was found that the demographics of
MSMEs in Indonesia for the average gender is
female, the provinces with the highest number of
MSMEs surveyed are the province of Java Island,
and most types of MSME businesses are
accommodation providers and food and beverage
providers. This study also conducted a descriptive
analysis of the use of four dimensions of innovation
that consists of product innovation, process
innovation, marketing innovation, and
organizational innovation. From the analysis,
marketing innovation was found to receive more
positive responses, hence to view more clearly the
use of marketing innovation in Indonesian MSMEs,
cross-tabulation was done.
From the cross-tabulation of marketing
innovation and demographic items especially in
gender, we find that women tend to agree more with
item MI1 (use of social media) because Indonesian
women tend to be more active in social media than
men. While men tend to agree more with MI2 (use
of marketplace) and items MI3 (use of delivery
service). Although the difference between men and
women is only 0.3% in MI2. It can be a positive
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sign for MSMEs because there is increasing
digitalization support in Indonesia, especially on the
issue of gender equality, as most MSME owners are
women. From the overall results, it shows that
gender equality in Indonesia is increasing rapidly
because increasingly more women are digitally
aware and understand the importance of
digitalization, and gender differences affect different
choices or preferences of marketing innovations.
7 Implications, Limitations, and
Suggestions for Further Research
In this study, the implication is that where
Indonesian MSME business owners go or have run
their business, they can use this study to understand
MSME businesses in Indonesia based on the type of
business, gender, and province. In addition, MSME
business owners can also apply items of marketing
innovation (use of social media, e-commerce, and
delivery services) that are appropriate based on
gender preference.
This study has several limitations, among others,
firstly, this research is cross-sectional, where data
collection is only done at one point in time, so this
study cannot capture all impacts of the pandemic on
MSMEs in Indonesia. Second, the data collection
method is designed using non-probability sampling,
where the data taken does not provide insight into
the quality of the representation of a population.
Therefore, the results of this study do not reflect the
situation of MSMEs in Indonesia. The author
suggests that future studies should consider several
factors, such as testing the sample data using other
methods. The sample data collection in this study
may be limited, and the imbalance in the sample
size distribution may affect the results. Thus, this
study can use a longitudinal study to examine long-
term variables so that the results have a high level of
validity.
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Creative Commons Attribution License 4.0
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WSEAS TRANSACTIONS on SYSTEMS
DOI: 10.37394/23202.2022.21.43
Marcella Astriani, Mariani, Angeline Clairine,
Mohammad Ichsan, Agung Sudjatmoko
E-ISSN: 2224-2678
399
Volume 21, 2022