theoretical ideas; rather, they are supported by actual
data and real-world instances.
4 RISK MANAGEMENT
Any supply chain that has to make decisions while
dealing with uncertainty does so in part by using a risk
management strategy. Information ignorance is the
source of risk, and many risk factors (e.g., COVID-
19), are uncontrollable by humans, but big data
analytics may help us create a robust supply chain
system that can strengthen the information system
and reduce risk (Araz et al., 2020). Big data analytics
can generally be used to protect against hazards
associated with shipping, default between merchants
and suppliers, dangerous chemicals during the
connection between recyclers and remanufacturers,
and environmental harm (Ghalehkhondabi et al.,
2020).
Risks in supply chain management (SCM) include
globalization, shorter product life cycles, demand
forecasts, cost pressures, outsourcing, and offshore.
The business environment is become more uncertain
as a result of the increasing complexity of SCM and
networks. These are supply chain risk events that
have an impact on the network as a whole. An
indication of a potential disruption to the supply chain
is a risk event. Global supply chains are more
vulnerable to risk and confront several obstacles.
Increased openness and information exchange
amongst supply chain actors are necessary for this.
Globalization and nations' economic interactions with
partner nations have altered global production
methods. Each of these raises the supply chain's risk
and complexity. Distribution centers are another
name for distribution centers in contemporary global
supply networks. The needs of buyers are fulfilled at
the operations center. Because their effectiveness
influences the overall SCM value, these centers must
be efficient. Pay close attention to how the disaster
affects the supply chain and make sure it has an effect
on operational performance as well. In the current
global marketplace, supply chain interruptions and
the related risks to operations and finances are among
the most urgent problems affecting rival businesses.
Still, there's a distinction between danger and
disruption. An indication of supply chain risk is
disruption. However, the risk is still remained
unaffected (Gurtu & Johny, 2021).
5 LIMITATIONS AND
PROSPECTS
Supply chain management is now much more
efficient thanks to big data analysis. Although supply
chain management can benefit greatly from
predictive analytics, there are certain drawbacks to its
application. First, historical records provide the data.
Inadequate historical data can have an impact on how
well predictive analysis works. The second issue is a
compatibility issue brought on by predictive analysis
tool upgrades. It will be possible to thoroughly
examine how the forecasting tool improvement
affects the forecasted results in the future.
There are also restrictions on this paper's use of
risk management. This document only chooses a
small number of key phrases; an article may go
unresearched if it does not have the word "risk" in its
title, keyword, or abstract. Further research on
particular under- or undiscovered areas can be
conducted using the summary results of this paper. It
is anticipated that this study of the literature will help
scholars investigate supply chain risk management
(SCRM) more thoroughly. The way supply chains
function across industries will continue to change as
a result of these applications. Supply chains will
depend more and more on big data analytics as
technology continues to change the world around us.
This will increase the reliance of these networks on
ubiquitous digital information at every link. Big data
analytics will play a significant role in the ongoing
development and improvement of the supply chain. It
may also provide solutions to the various issues that
various sectors are facing as a result of market trends.
The foundation of the world economy, supply chains
promote trade, consumption, and growth in the
economy.
6 CONCLUSIONS
To sum up, the foundation of the world economy,
supply chains promote trade, consumption, and
growth in the economy. The rapid advancement of
modern information technology has made data an
essential basis for the development of manufacturing
supplies and techniques. In this study, the architecture
of big data services, some existing big data
application scenarios, and predictive analytics based
on big data and risk management services are
analysed. This study first provides an overview of the
history, state of development, and future prospects of
SCM. The big data analysis technology and its