ANALYSIS OF THE IMPACT OF DIGITAL
TRANSFORMATION ON ECONOMIC PRODUCTIVITY IN THE MANUFACTURING INDUSTRY SECTOR IN
TANGERANG REGENCY
Jhonny1, Pudji Astuty2
1, 2 Universitas Borobudur
[email protected]1, [email protected]2
|
KEYWORDS digital transformation, economic
productivity, manufacturing industry sector |
ABSTRACT This
study aims to explore the influence of digital transformation on economic
productivity in the manufacturing industry sector in Tangerang Regency. Using
observation and questionnaire methods, this study focused on companies that
have implemented digital technology in their production processes. Data were
analyzed using Pearson correlation tests and linear regression, which showed
a significant positive relationship between the implementation of digital
transformation and increased company productivity. These findings confirm
that the use of digital technology, such as process automation and
information system integration, has a direct impact on increasing operational
efficiency and the company's ability to produce higher output. However,
behind this positive potential, the study identified several challenges in
companies, such as high initial investment costs and the need for intensive
training for employees to adapt to new technologies. These obstacles are
especially felt by small and medium-sized companies that have limited
resources. Therefore, this study suggests the importance of strategic support
from the government, such as subsidies or training programs focused on
digitalization. In addition, companies need to develop internal strategies to
prepare technology infrastructure and improve employee competencies to be
better prepared to face the digital era. In conclusion, digital
transformation is a strategic step to strengthen the competitiveness of the
manufacturing industry in Tangerang Regency and can be a model for wider
implementation to improve economic competitiveness at the national and global
levels. |
INTRODUCTION
The development of the digital world today has affected almost
every aspect of life, changing people's interactions, work, and businesses (Schmidt & Cohen, 2015). This transformation is not limited
to sectors that are traditionally connected to information technology, such as
banking or communication services, but also extends to all economic sectors,
including education, health, agriculture, and manufacturing. Each sector is
encouraged to adapt and integrate digital technology into its operations. It is
done to improve efficiency, service quality, and competitiveness in facing
increasingly dynamic market demands. The technologies usage such as big data,
artificial intelligence, and automation is no longer an option, but a necessity
for companies to survive and thrive amidst global competition (Chui & Francisco, 2017).
Digital developments have also brought about a new era that has
significantly changed the business paradigm. In the past, technology was only
seen as an optional tool to complete certain jobs (Sheninger, 2019). However, now technology has evolved
into an integrated element in all business processes (Harmon, 2019). This ongoing technological era
requires every organization to carry out digital transformation as a strategic
step (Hanelt, Bohnsack, Marz, & Antunes Marante, 2021). Companies will be left behind and
lose their competitive position if they fail to follow digital trends risk (Ashurbayev, Rasulova, Abduq axxorova, & Nazirova,
2024). For example, in the manufacturing industry,
technologies such as the Internet of Things (IoT), robotics, and smart
manufacturing have transformed the way production, supply chain management, and
asset maintenance are carried out. The use of these technologies not only
increases productivity but also creates significant efficiencies by minimizing
human error and maximizing resource utilization (Ni�etić et al., 2019).
Digital transformation is no longer just an additional option but
has become a necessity that must be implemented by all sectors, including the
manufacturing industry (Butt, 2020). The business world has entered a
new era, where technology is not only a differentiating factor but also a
determinant of success. Companies that cannot adapt to these changes will find
it difficult to compete because digitalization opens up vast opportunities for
new players with more innovative business models (Linz et al., 2017). Therefore, every business actor
needs to continue to monitor technological developments, invest in digital
transformation, and ensure that they utilize technological innovation optimally (Teece, 2018). This technological era requires
every sector to be more dynamic, responsive, and ready to continue transforming
along with rapid digital developments.
The manufacturing industry is one of the key sectors that
significantly drive Indonesia's economic growth (Asmara, 2018). Its role is not only limited to
increasing economic value but also has a major impact on creating extensive employment
opportunities and increasing state revenues. The main advantage of this sector
is its ability to process raw materials into finished products that have high
added value, which are not only in demand domestically but also able to compete
in the global market. It makes the manufacturing industry one of the stable
sources of foreign exchange for Indonesia. In addition, the manufacturing
sector has a broad scope, covering various fields such as the metal industry,
food and beverage, transportation, machinery and equipment, chemicals,
pharmaceuticals, and electronics. Each field has a strategic role in advancing
the economy and spurring the growth of other related sectors.
The manufacturing industry expansion in Indonesia continues to
experience a stable increase along with the increasingly diverse market needs.
Data from the Central Statistics Agency (BPS) in 2023 showed that there was a
growth in the manufacturing industry of 4.64%.
The manufacturing industry plays an
important role in driving the regional economy, especially in strategic areas
such as Greater Tangerang. With an area of around 1,500 km2 and a
population of more than 5 million, this area is a significant center of
industrial activity in Indonesia. Greater Tangerang is divided into three
autonomous regions, namely Tangerang Regency, Tangerang City, and South
Tangerang. This area is often referred to as the "1,000 industries"
area due to the high concentration of factories and manufacturing companies,
especially in areas such as Balaraja, Cisoka, and Cikupa. The existence of this
diverse industry makes Greater Tangerang one of the centers for the development
of the manufacturing sector which plays a major role in creating jobs,
attracting investment, and supporting regional and national economic growth.
The development of the manufacturing
industry cannot be separated from the important role of workers who collaborate
well to achieve maximum performance. Solid cooperation between them is a major
factor in increasing productivity and economic growth in this sector.
Productivity has a very significant meaning because this concept is closely
related to economic growth. In general, productivity is often discussed sources
of economic growth topics, because the ability of an industry to produce more
goods or services with existing resources is one of the keys to success. If
workers can work effectively and efficiently and are supported by good economic
management, then industrial income can increase, and this contributes
positively to national economic growth.
Economic growth is one of the main
indicators that shows the results of development that has been carried out by a
country. In addition to being a benchmark, economic growth also helps determine
the direction of future development policies. Factors that influence economic
growth include various aspects, such as the accumulation of capital invested in
land, machinery, and other infrastructure, utilization of natural resources,
and the quality of human resources in terms of quantity and skills. In
addition, technological advances, good access to information, innovation, and
the ability to continue to develop themselves also play an important role. A
positive work culture and an open attitude to change are the keys for the
manufacturing sector and the economy, in general, to continue to grow and
compete in the global market.
The rapid development of the digital world
has changed the direction and dynamics of the industrial sector, including the
manufacturing industry. Digital transformation can be interpreted as the
comprehensive application of digital technology that enables the creation of
innovations and creativity in a field, not just supporting existing
conventional methods (Vezyridis et al., 2011). According
to Verhoef et al. (2021), digital
transformation is a process of change that utilizes digital technology to
develop new business models that can create and provide added value for the
company. This process not only focuses on internal development, but also
improves customer experience, and operational efficiency, and changes the
business model to create more value for customers (Morakanyane et al., 2017). Thus,
digital transformation is the main key for companies to adapt and remain
competitive in this modern era.
Based on the discussion above, two main
problems can be formulated that need to be considered in the development of the
manufacturing industry. First, how to increase the productivity and
competitiveness of the manufacturing industry amidst rapid digital change to
encounter global competition and meet increasingly complex market needs?
Second, what is the right strategy to optimally utilize digital transformation
in the manufacturing sector without ignoring important aspects such as human
resource management, product quality, and industrial sustainability? Answering
these two problem formulations will be an important step in ensuring that the
manufacturing sector can play a more optimal role as the main pillar of the
national economy.
METHOD�� RESEARCH
1. Population
and Sampling
The population of this study includes all
large and medium-scale manufacturing companies in Tangerang Regency. According
to data from the Central Statistics Agency (BPS) of South Tangerang City in
2014, there were around 1784 companies in this sector operating in the area.
The high number of companies indicates that Tangerang Regency is one of the
main industrial centers in Banten Province, with various sectors such as metal,
food and beverage, textile, chemical, and electronic equipment. This population
is the main target in the study, considering the large contribution of the
manufacturing sector to the regional economy, as well as its strategic role in
the development of the industry as a whole. The selection of this population is
based on the availability of representative and relevant data to measure the
impact of digital transformation on economic productivity in the manufacturing
industry sector. However, this study will not use all companies as research
objects but will focus on several samples for this investigation.
The appropriate sampling method according
to the researcher is Stratified Random Sampling. The method is used because the
study population is in various manufacturing industry companies (metal, food
and beverage, textile, chemical, and electronic sectors) with various business
scales (large and medium industries). Stratified Random Sampling allows
researchers to divide the population into strata based on relevant categories,
such as industry type and company scale. After that, sampling is carried out
randomly from each stratum so that each category is proportionally represented
in the research sample. This method is very suitable to ensure that the unique
characteristics of each stratum in the population can be analyzed in more depth
so that the research results can provide a more accurate picture of the impact
of digital transformation on economic productivity in the manufacturing sector
in Tangerang Regency.
2. Research
Instrument
The instrument that will be used in this
study is a questionnaire method, which is in line with the title of this study.
The questionnaire aimed to obtain quantitative data from involved company
leaders and workers in the digital transformation process. In addition, this
study also used a questionnaire designed to measure respondents' perceptions
regarding the effectiveness of using digital technology, the obstacles faced,
and its impact on individual productivity and overall company performance. The
research questionnaire that the researcher will use is a questionnaire adapted
from the Kontić & Vidicki (2018) questionnaire. In the questionnaire
compiled by Kontić & Vidicki (2018), there are
three main components that are the focus, namely Digital Mindset consisting of
2 questions, Practices consisting of 4 questions, and Data Access Integration
with 3 questions. Each of these points is designed to measure the extent of the
application of digital mindsets, digital-based work practices, and the
company's ability to integrate data access efficiently to support digital
transformation in the organization. So, the number of questionnaires used to
assess digital transformation is 9 queries. The second questionnaire is a
questionnaire used to measure the scale of economic productivity. The
questionnaire for the economic productivity variable uses a total of 12
questions.
3.
Research
Procedures and Timeline
This research begins with a preliminary
study to identify manufacturing companies in Tangerang Regency that have
implemented digital technology. Furthermore, questionnaires are distributed to
respondents who meet the established criteria, and the estimated time for
filling out the questionnaire is estimated to take around 1-2 weeks. After all
questionnaires have been collected and analyzed initially, in-depth interviews
are conducted with several key informants to deepen understanding of the
initial results. The entire research process, which includes data collection,
analysis, and preparation of research report results, is expected to be
completed within 3-4 months, which means that this research will be conducted
from September to December 2024.
4.
Analysis
Plan
The analysis plan that will be done in this
study is to process the data obtained through the questionnaire which will be
analyzed quantitatively using descriptive statistical methods. This approach
involves calculations such as averages and standard deviations, correlation and
regression tests to evaluate the relationship between digital transformation
variables and economic productivity. Meanwhile, data collected from
observations will be analyzed qualitatively using thematic analysis techniques,
which aim to identify the main patterns in the implementation of digital
transformation in the field and understand the dynamics that occur in the
application of technology in the manufacturing industry. In addition, this
study will be supported or assisted by the SPSS 25 application to test the
level of validity and reliability of the questionnaire that will be used in
this study. In addition, researchers will use SPSS 25 to see
5.
Validity and
Reliability Test
To ensure the validity and reliability of
the instrument used in this study, the researcher will conduct a validity test
and a reliability test on the questionnaire used. Validity testing is used to
assess whether a questionnaire can measure what should be measured so that it
can be said to be valid (Ghozali, 2012). The
validity of the questionnaire can be tested by comparing the calculated r-value
to the r table at the degree of freedom (df) = n-2, where n is the number of
samples, and the significance (alpha) used is 0.05. If the calculated r value
is greater than the r table and has a positive value, then the questions or
indicators in the questionnaire are considered valid (Ghozali, 2012).
Reliability testing is a test used to
measure a questionnaire which is an indicator of a variable or construct. A
questionnaire is said to be reliable if a person's answer to the statement is
consistent or stable over time Ghozali (2012). In this
Reliability Test, Cronbach's Alpha method will be used, which functions to
measure the internal consistency of each item on the instrument. A Cronbach's
Alpha value of more than 0.6 indicates that the instrument is reliable.
6.
Statistic
and Comparative Tests
The statistical methods used in this study
include the Pearson correlation test which is used to measure the level of
relationship between digital transformation variables and economic
productivity. In addition, linear regression analysis will be applied to
evaluate the influence of the independent variable (digital transformation) on
the dependent variable (economic productivity). If necessary, the ANOVA test
will analyze the differences in the influence of digital transformation across
company scales. These statistical techniques were chosen to determine whether
there is a significant relationship between the variables studied and to
measure how strong the existing influence is.
7.
Scope and
Limitations of the Study
The scope of this study is limited to
manufacturing companies in Tangerang Regency that have adopted digital
technology. Therefore, the findings of this study cannot be considered
representative of the entire manufacturing industry sector in Indonesia. In
addition, the focus of this study is only on measuring the impact of digital
transformation on economic productivity without covering other aspects that may
be relevant.
RESULT
AND DISCUSSION
The validity test
results for the questionnaire used in this study include 9 questions designed
to assess aspects of digital transformation. This questionnaire measures
various dimensions of digital technology implementation in companies, including
digital mindset, work practices, and data access integration. Each question is
tested to ensure that it truly reflects the concept to be measured. The results
show that all questions have good validity, so they can be used with confidence
to evaluate the impact of digital transformation in the industrial sector. In
addition, the questionnaire on industrial economic productivity consists of 12
questions designed to measure factors that contribute to the economic
performance of companies. Cronbach's Alpha method was used to ensure the
reliability of this questionnaire, a reliability test was also conducted. The results
of the reliability test showed satisfactory values, where all questions
achieved a Cronbach's Alpha value above 0.7, indicating that the instrument has
good internal consistency. Thus, this questionnaire can be relied on to provide
valid and consistent data in assessing the impact of digital transformation on
economic productivity.
The next test is a
statistical test used in this study which after going through testing showed a
significant relationship between digital transformation and economic productivity
in the manufacturing industry sector. Using the Pearson correlation test, data
analysis showed a p-value of less than 0.05, indicating a strong positive
correlation between the two variables. Furthermore, the linear regression
analysis applied showed that digital transformation had a significant positive
effect on economic productivity, with the R-squared value indicating how much
productivity variability could be explained by the digital transformation
variable. In addition, the ANOVA test conducted to test the differences in the
effect of digital transformation across various company scales showed
consistent results, where larger companies tended to have higher levels of
productivity along with the implementation of digital technology. These findings
provide strong evidence that investment in digital transformation not only
improves operational efficiency but also contributes significantly to the
economic performance of the industry.
The results of this
study indicate that there is a significant relationship between digital
transformation and economic productivity in the manufacturing industry sector
in Tangerang Regency. This finding line-up with previous studies that emphasize
the importance of digital technology in improving operational efficiency and
company competitiveness (Brynjolfsson & McAfee, 2014). The
application of digital technologies such as automation, data management, and
integration of information access has been shown to increase the speed and
quality of production, which in turn contributes to increased productivity.
This shows that companies that adopt digital transformation tend to perform
better in facing competition in the global market.
However, challenges in
implementing digital technology also need to be discussed. Many companies still
face obstacles, such as a lack of trained human resources, high initial investment
costs, and resistance to change from within the organization (Westerman et al., 2014). This study
highlights the importance of change management and employee training to ensure
the success of digital transformation. Recommendations for further research include
delving deeper into other factors that may influence the effectiveness of
digital transformation, such as corporate culture and the business strategy
implemented. In conclusion, digital transformation is a crucial step for
manufacturing companies in Tangerang Regency to increase productivity and
competitiveness in the industrial era.
CONCLUSION
The study's findings
affirm that digital transformation significantly enhances economic productivity
within the manufacturing industry sector in Tangerang Regency. Statistical
tests reveal a positive correlation between the adoption of digital technology
and increased operational efficiency and economic output. Companies embracing
digital technology demonstrate superior performance in operational efficiency and
competitiveness, both locally and globally. Digital transformation empowers
companies to promptly respond to market demands and expedite the production
process, directly contributing to economic expansion. Nonetheless, challenges
such as the necessity for high-quality human resource training hinder some
companies. Thus, the success of digital transformation is heavily reliant on
the company's internal readiness, encompassing change management and technology
adaptation. This study underscores the significance of aiding companies,
particularly those of medium and small scale, in their digitalization journey.
Therefore, digital transformation is not only pivotal for augmenting economic
productivity but also for fortifying the manufacturing sector's competitiveness
in the future.
REFERENCES
Ashurbayev, O., Rasulova, G., Abduqaxxorova, S., &
Nazirova, R. (2024). Influence Of Market Trends On The Failure Of Businesses. Образование
Наука И
Инновационные
Идеи В Мире, 56(4), 74�83.
Asmara, K. (2018). Analisis peran sektor industri �manufaktur terhadap penyerapan
tenaga kerja di Jawa Timur. Journal of
Economics Development Issues, 1(2),
33�38.
Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and
prosperity in a time of brilliant technologies. WW Norton & company.
Butt, J. (2020). A conceptual framework to support digital
transformation in manufacturing using an integrated business process management
approach. Designs, 4(3), 17.
Chui, M., & Francisco, S. (2017). Artificial intelligence
the next digital frontier. McKinsey
and Company Global Institute, 47(3.6),
6�8.
Ghozali, I. (2012). Pembelajaran Musik Berbasis Siswa Dengan
Pendekatan Local Genius. Jurnal Visi
Ilmu Pendidikan, 7(1).
Hanelt, A., Bohnsack, R., Marz, D., & Antunes Marante, C.
(2021). A systematic review of the literature on digital transformation:
Insights and implications for strategy and organizational change. Journal of Management Studies, 58(5), 1159�1197.
Harmon, P. (2019). Business
process change: a business process management guide for managers and process
professionals. Morgan Kaufmann.
Hermiza, M., & Apriyanto, M. (2023). http://ejournal.
kemenperin. go. id/bbihp/article/view/8018/6188. Jurnal Industri Hasil Perkebunan.
Kontić, L., & Vidicki, Đ. (2018). Strategy for
digital organization: Testing a measurement tool for digital transformation. Strategic Management, 23(1), 29�35.
Li, L. (2018). China�s manufacturing locus in 2025: With a
comparison of �Made-in-China 2025� and �Industry 4.0.� Technological Forecasting and Social Change, 135, 66�74.
Linz, C., M�ller-Stewens, G., & Zimmermann, A. (2017). Radical business model transformation:
Gaining the competitive edge in a disruptive world. Kogan Page
Publishers.
Morakanyane, R., Grace, A. A., & O�reilly, P. (2017). Conceptualizing digital transformation in
business organizations: A systematic review of literature.
Ni�etić, S., Djilali, N., Papadopoulos, A., &
Rodrigues, J. J. P. C. (2019). Smart technologies for promotion of energy
efficiency, utilization of sustainable resources and waste management. Journal of Cleaner Production, 231, 565�591.
Schmidt, E., & Cohen, J. (2015). The new digital age: Reshaping the future of people, nations and
business. SAGE Publications Sage India: New Delhi, India.
Schneider, S., & Kokshagina, O. (2021). Digital
transformation: What we have learned (thus far) and what is next. Creativity and Innovation Management,
30(2), 384�411.
Sheninger, E. (2019). Digital
leadership: Changing paradigms for changing times. Corwin Press.
Teece, D. J. (2018). Profiting from innovation in the digital
economy: Enabling technologies, standards, and licensing models in the wireless
world. Research Policy, 47(8), 1367�1387.
Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A.,
Dong, J. Q., Fabian, N., & Haenlein, M. (2021). Digital transformation: A
multidisciplinary reflection and research agenda. Journal of Business Research, 122, 889�901.
Vezyridis, P., Timmons, S., & Wharrad, H. (2011). Going
paperless at the emergency department: A socio-technical study of an
information system for patient tracking. International
Journal of Medical Informatics, 80(7),
455�465.
Westerman, G., Bonnet, D., & McAfee, A. (2014). Leading digital: Turning technology into
business transformation. Harvard Business Press.
�
Copyright holders:
Author�s Name (Year)
First publication right:
Hawalah � Kajian Ilmu Manajemen, Ekonomi dan Bisnis
This
article is licensed under a Creative Commons Attribution-ShareAlike 4.0
International