IOT FINANCIAL MANAGEMENT SYSTEM
FOR ENERGY ENTERPRISE MANAGEMENT
RISK AND PREVENTION AND CONTROL
STRATEGY UNDER THE BACKGROUND OF
DOUBLE CARBON
Rui Cui*
School of Economics, Jiangsu University of Technology, Changzhou, Jiangsu,
213001, China.
cuirui0622@126.com
Reception: 02/02/2023 Acceptance: 13/04/2023 Publication: 28/06/2023
Suggested citation:
Cui, R. (2023). IOT financial management system for energy enterprise
management risk and prevention and control strategy under the
background of double carbon. 3C Empresa. Investigación y pensamiento
crítico, 12(2), 144-159. https://doi.org/10.17993/3cemp.2023.120252.144-159
https://doi.org/10.17993/3cemp.2023.120252.144-159
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Ed. 52 Iss.12 N.2 April - June, 2023
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ABSTRACT
Despite the absolute number of developments and products of enterprise
management systems and platforms, there are still limited ways to achieve risk
assessment of enterprise financial management by energy enterprise stakeholders.
To reduce the financial management pressure of energy enterprises as well as to
reduce enterprise financial risks, this paper establishes an Internet of Things(IOT)
financial management system. The system was also comprehensively evaluated
based on the financial risk management status of each company for the period
2016-2020. The results show that a significant increase in the share of non-current
liabilities was observed after the introduction of the IOT-based financial management
system in 2018. Relative to the 2017 data, the current liability ratio decreased by
2.96%, 7.98%, and 14.59% for 2018, 2019, and 2020, respectively. The ratio of
corporate investments to revenue decreased by 8.74%, 22.91% and 16.83%,
respectively. Investments as a percentage of earnings decreased by 6.22%, 5.48%,
and 6.82%, respectively. The ratio of undistributed earnings decreased by 9.69%,
18.82% and 35.39%, respectively. Finally, the introduction of the IOT's financial
management system reduced financial management costs by a factor of 2.822, 4.358
and 5.501, respectively. And the cost of managing people in an integrated manner
was reduced by 2.964, 3.012 and 4.004 times respectively.
KEYWORDS
IOT engineering; financial management; low-carbon energy; risk assessment; carbon
daub
INDEX
ABSTRACT
KEYWORDS
1. INTRODUCTION
2. OVERVIEW OF THE INTERNET OF THINGS (IOT) FINANCIAL MANAGEMENT
SYSTEM
2.1. The functional division of the IOT financial management system
2.2. Main module functional description
2.3. User characteristics and system application scenarios
3. INDICATOR WEIGHTING
4. ANALYSIS AND DISCUSSION
4.1. IOT-based risk assessment impact
4.2. The overall impact of IOT-based business development
5. CONCLUSION
REFERENCES
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1. INTRODUCTION
Global climate change has led to sea level rise and frequent extreme weather
disasters on Earth [1-2]. Biodiversity is severely affected, and global climate change
has brought serious adverse impacts to human society [3-4]. More importantly, many
of the adverse effects are already frequently visible and the situation is becoming
increasingly critical [5]. Recent disasters such as extreme droughts and persistent
forest fires due to superheated temperatures in North America, persistent heavy rains
and floods in Western European countries, persistent heavy rains in many parts of
northern China, and other natural disasters are most likely related to global climate
change [6-7]. To actively respond to climate change, China has explicitly proposed the
strategic goal of carbon peaking and carbon neutrality [8]. Carbon peaking and carbon
neutrality will change China's energy and industrial structure, reducing the share of
high consumption, high input, and high pollution industries [9-10]. Rather than simply
sacrificing economic growth and national wealth accumulation, carbon peaking and
carbon neutrality will lead to a comprehensive, coordinated, sustainable and high-
quality development under carbon emission reduction constraints. The investment in
"dual carbon" is both an expense and an opportunity for economic transformation and
development [11]. The economic development mode will also shift to a green and
sustainable development model. All activities of human society have been inseparable
from energy, from clothing, food, housing and transportation to culture and
entertainment, all of which consume a certain amount of energy directly or indirectly
[12]. Energy is the material basis for the survival and development of human society
[13]. Energy is the blood of industrial development, which drives the operation of
industry-. Therefore, it is essential to achieve the goal of carbon peaking and carbon
neutrality in a way that will affect the development of energy companies.
Energy as a strategic resource has a particularly important position in global
economic development and has a wide and far-reaching impact on many aspects of
international politics, military, science and technology [15-22]. China is not only a
major energy producer but also a major consumer in the world, and with the rapid
development of the Chinese economy, it is facing enormous pressure in terms of
energy demand [23]. Especially under carbon-peaking and carbon-neutral policies,
China's energy development model needs to be adjusted accordingly. The study of
the interrelationship between the economic growth of energy companies, financial
risks and the implementation of the carbon peaking policy is an important guide for the
development of the national economy. Lu, S. [24] conducted an in-depth study on the
impact of carbon peaking policy on energy funds, using a sample of 231 energy funds
in China between 2008 and 2019, and examined the effect of carbon peaking policy
on the network herding effect of energy funds as measured by hybrid network
centrality, as well as the herding effect on profitability and stability. The results show
that the network herding effect has a positive impact on the short-term profitability and
risk-resilience of energy funds. However, the network herding effect reverses when
long-term stability is tested. On the contrary, it can trigger greater systemic risks. Li, T.
25] evaluated the environmental performance of thermal power enterprises by
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considering peak carbon. They constructed an index system that comprehensively
considered the whole process of environmental management of power generation
enterprises and the factors affecting the environment. The environmental performance
of thermal power enterprises was evaluated comprehensively by factor analysis, and
then comparability of the environmental performance of power generation enterprises
was achieved. This study enables timely, accurate, and comprehensive monitoring by
stakeholders such as the government and the public. Cui, X 26] proposed an energy
consumption prediction model based on an improved whale algorithm to optimize a
linear support vector regression machine. The model combines multiple optimization
methods to overcome the shortcomings of traditional models. They used the model to
forecast the improvement of China's energy consumption under the peak carbon
target. The results concluded that China needs to adjust its current policies to achieve
the peak carbon target. Lin, J. [27] developed a three-level economic-environmental-
behavioral demand response model for incentive price setting. Their model extends
the analysis beyond the traditional disciplines of economic entities and incorporates
new customer psychological cues. The findings suggest that through a reasonable
carbon price, demand response models can be an effective tool to improve energy
efficiency and decarbonization. Chen, J. [28] argued that the energy supply and
demand model for China includes a planned peak scenario and an advanced peak
scenario, which are designed by taking into account China's economic development,
technological progress, policies, resources, and environmental capacity. In addition,
they argue that decarbonization will become a fundamental feature of the structural
change in energy supply and demand. The realization of the carbon peak requires the
joint efforts of all industries. However, based on carbon peak realization, we need to
consider the development of energy companies. With the promotion of the smart city
concept, every industry in the city needs to become smarter. Ban, Y. [29] proposed an
energy management system that can be used to monitor energy consumption in real-
time, keep track of the company's energy consumption, and allocate the company's
energy consumption. They developed two functions in the energy management
system, energy allocation and energy consumption prediction, so energy companies
can get better production plans, reduce their energy consumption, and improve their
competitiveness. Considering the physical limitations of different energy networks,
Mirzaei, M.A. [30] proposed a new entity called Multi-Energy Distribution Company.
They argue that multi-energy storage systems and integrated demand response are
considered to increase the flexibility of multi-energy distribution companies to serve
multiple energy demands. Wang, L. [31] analyzed supply chain financing and
blockchain technology for energy companies based on theoretical studies. They
analyzed the management system, cash flow, and risk control system of the supply
chain in the context of the current specifics of blockchain in supply chain financing.
The results show that the supply chain financing parties of energy enterprises can
optimize the supply chain financing risk control system while reducing business costs
and improving enterprise efficiency, which greatly reduces the risk of the supply chain
financing parties of energy enterprises and thus improves the competitiveness of
enterprises. Zhang, X. [32] argues that effective financial management of prepayment
is an important option for service providers and customers' financial IoT. They propose
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a scalable accounting solution where each user where the hosting user is located
occupies a prepaid account that forms part of an embedded system, thus better
serving each financial customer and reducing financial risk. From the above analysis,
we can see that the realization of the carbon peak requires the joint efforts of all
industries. The implementation of the peak carbon policy has a significant impact on
the economic profitability of energy companies and the structure of energy sales.
Therefore, in the context of the carbon peak, energy companies need to be prepared
in advance for the arrival of financial risks and to do a good job of prevention and
control.
The financial management risks and prevention and control of energy enterprises
need to control and manage the financial risks and financial crises that may occur in
advance. The traditional financial risk and financial crisis control and management
methods have some shortcomings, such as low efficiency, slow speed, high accuracy
and so on. Therefore, in this study, we introduce the Internet of Things financial
management system to unify the management and prevention of financial
management risks of energy enterprises. It focuses on the financial management of
energy enterprises, financial risk assessment of energy enterprises, financial
statistical statements of energy enterprises, basic financial data of energy enterprises,
financial query of energy enterprises and protection of financial management system
of energy enterprises. We hope our research can contribute to reducing the financial
risks of energy enterprises and improving the core competitiveness of energy
enterprises in the context of the carbon peak.
2. OVERVIEW OF THE INTERNET OF THINGS (IOT)
FINANCIAL MANAGEMENT SYSTEM
With the increasing complexity of the financial management of energy enterprises,
this study provides unified management of energy enterprise finance by enterprises
and institutions through IOT financial management system. IOT financial management
system is a study of risk and prevention and control strategies of energy enterprise
financial management based on the background of Carbon Dafeng and the
comprehensive use of modern information technology, and there are unique designs
and innovations in all stages of IOT financial management system [33, 34]. The main
manifestations are as follows.
1.
Advanced. Through the IOT financial management system, most of the
operations such as asset transfer, allocation and contract information signing in
the past financial management of energy enterprises are dispersed to various
departments of energy enterprises to complete, which makes the financial
management of energy enterprises less stressful and makes the work risk of
the original enterprise financial management reduced.
2.
Structured. the IOT financial management system is based on the current
financial management system of energy enterprises and the prevalent unit
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establishment status, based on a tree structure for an intuitive representation
of financial management, eliminating the authority of the internal level of
energy enterprises and maximizing the time saving of energy enterprise
finance operations.
3. Comprehensiveness. the IOT financial management system can handle
different types of management affairs in parallel by incorporating the financial
management risks in the context of carbon peak into the financial management
system for unified management, which not only facilitates the operation of
enterprise personnel but also can reflect the financial management status of
energy enterprises comprehensively.
2.1. THE FUNCTIONAL DIVISION OF THE IOT FINANCIAL
MANAGEMENT SYSTEM
IOT financial management systems can be divided into client, server and mobile
through C/S architecture. The client side of the IOT financial management system is
mainly divided into four functional modules: financial management of energy
enterprises, financial risk assessment of energy enterprises, financial statistics and
reports of energy enterprises, and basic financial data of energy enterprises. The IOT
financial management system is divided into two functional modules, namely,
downloading financial information of energy enterprises and returning financial
information of energy enterprises.
Figure 1. The functional division of IOT financial management system
2.2. MAIN MODULE FUNCTIONAL DESCRIPTION
IOT's financial management system will manage the finance of energy enterprises
comprehensively, including: financial information registration, financial information
inventory, financial contract changes, financial depreciation and financial information
reports, a total of five major functions.
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1.
Financial information registration. Users register the financial information of
energy enterprises and institutions through mobile smart devices and transmit
the data back to the database of the IOT financial management system
through Web Service, and then improve the user details through financial
information registration, which provides convenience for the management of
back-end technicians of energy enterprises.
2.
Financial information inventory: IOT financial management system takes
inventory of financial information, replacing the time-consuming and laborious
manual financial information inventory and tedious financial data recording,
saving the labor cost and time cost of financial data inventory.
3.
Financial contract changes, IOT financial management system facilitates the
processing of changes to the important information of financial contracts and is
used to record the changes of information after the review of energy company
leaders.
4.
Financial depreciation, IOT financial management system for automatic
depreciation of financial data, the user only needs to regularly upload the data,
eliminating the work of manual calculation and reduce the calculation of human
error in the process of calculation, not only to reduce the data depreciation
processing time but also to improve the accuracy of depreciation calculation
rate.
5.
Financial information report: IOT financial management system organizes the
collected financial information and provides report service for energy enterprise
management certificate so that managers can understand the information
about fixed assets at all times.
2.3. USER CHARACTERISTICS AND SYSTEM APPLICATION
SCENARIOS
The basic features of the IOT financial management system established in this
paper are that it requires a simple operation to achieve its expected results, has a
simple user interface, and practical office functions. The main objective of the IOT
financial management system is to reduce the financial management pressure of
energy companies and reduce the financial management risks of the companies.
Based on the background of Carbon Dafeng, we conclude that the IOT financial
management system needs to achieve two major functions: identity identification and
information query. The former, through the electronic tags attached to the various
types of finances of energy enterprises, realize the scientific classification of the
finances of energy enterprises, as well as the detailed financial information records
and the identification of energy enterprise employees. It is convenient for the relevant
personnel of energy enterprises to assess the enterprise's financial management risks
and put forward prevention and control strategies.
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3. INDICATOR WEIGHTING
This paper uses an analytic hierarchy process to calculate the weight of each index
in the evaluation system [35, 36]. By sending questionnaires to 100 experts in the field
of financial management risks and prevention and control strategies, the importance
of the selected factors was compared. See Table 1 for the scores of financial
management evaluation indicators of energy enterprises.
Table 1. Scoring of financial management evaluation indicators of energy enterprises
In summary, the judgment matrix of the financial evaluation indicators and the first-
tier indicators of capital concentration capacity, operating service capacity, profitability,
and risk management capacity are as follows.
(1)
Among them, A1 is the financial evaluation index. This paper calculates the product
of each row element of judgment matrix A1 based on hierarchical analysis and
calculates its n root , and the calculation process is as follows.
(2)
(3)
Where is the element of the row and column of the judgment matrix . We
obtain the corresponding weight coefficients by summing up the square roots of the
above equation.
4. ANALYSIS AND DISCUSSION
Among the economic control tools that drive the energy revolution, energy
companies of all types prefer to have active and motivated employees and policy
regulation within their own companies. Despite the absolute number of information
Financial evaluation
indicators
Capital
concentration
capacity
Business
Service
Capability
Profitability Risk Management
Capability
Capital concentration
capacity
2 3 4 2
Business Service
Capability
1 4 1 5
Profitability 4/5 2 3 1
Risk Management
Capability
1 3 4 2
A1=
2 3 4 2
1 4 1 5
4
5231
1 3 4 2
Ai =∏aij
¯
Ai=nAi
aij
i
j
A1
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and advice and control tools, there are still relatively limited and few ways to build a
unified information and control system that allows energy companies to assess the
risks of corporate financial management and propose prevention and control
strategies for their personnel. It is still in the stage of development, but all of the
employee engagement-type policy tools are distributed in this area. On the road to
promoting low-carbon energy transition, the country hopes that energy-based
enterprises will also take the initiative to participate and jointly promote the goal of
carbon peak and carbon neutral strategy. Since the green and low-carbon transition of
industries is mainly done by organizations such as enterprises, it is more direct and
efficient to use more rigid policy tools such as regulation. In addition, energy
enterprises hope that by providing a good business environment, political
environment, legal environment, etc., the employees of enterprises and also the
development team will vigorously carry out scientific and technological research and
innovation in the field of energy-saving technology, carbon sink technology, etc., to
promote the better implementation of the Carbon Dafeng carbon neutral policy.
Therefore, this paper establishes an IOT financial management system to reduce
the financial management pressure of energy enterprises as well as to reduce the
financial risks of enterprises. At the same time, it can also facilitate the personnel of
energy enterprises to assess the enterprise's financial management risks and propose
prevention and control strategies. In the analysis of this section, we conducted pilot
experiments for several representative energy enterprises in Guangdong Province,
China. We replace the financial management system of the target pilot energy
enterprises with the IOT financial management system proposed in this paper and
count the current status of financial risk management of each enterprise in the period
of 2016-2020. The detailed aspects of the statistics are collected and assessed at four
levels: financing, investment, operation and revenue distribution. We not only use a
combination of statement analysis and indicator analysis but also will use a
combination of horizontal and vertical comparisons.
4.1. IOT-BASED RISK ASSESSMENT IMPACT
Specifically, we put the built IOT financial management system to test at the pilot
company in 2018, and collected and comprehensively evaluated data at four levels:
funding, investment, operation and revenue distribution of the company. The results
are shown in Figure 2. It is worth noting that in order to analyze the financial
management of energy companies in the context of carbon peaking, several new
energy companies are analyzed in this paper. Among them are representative new
energy technology companies such as electrochemical energy storage, solar energy
utilization and air energy storage. In terms of financing risk, the scale of liabilities of
selected energy companies gradually expands in 2016-2020, with both current and
non-current liabilities increasing in amount. However, in terms of the percentage of
total liabilities, it is clear that energy companies are still dominated by current
liabilities. In both 2016 and 2017, the proportion of current liabilities of enterprises
reached more than 95%, which makes the financing means of enterprises relatively
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single. and leads to a higher risk of financing. And after the introduction of the IOT-
based financial management system in 2018, a significant increase in the share of
non-current liabilities was observed. Relative to the data from 2017, the share of
current liabilities decreases by 2.96%, 7.98% and 14.59% in 2018, 2019 as well as
2020, respectively. As new energy technology is currently in a market with large
economic and product fluctuations, the reduction in current liabilities is more beneficial
to the long-term development of new energy technology companies in the current
economic and policy context of China new energy companies. And the fixed liabilities
that can be transformed into state funds are more conducive to the stability of new
energy company financing. In conclusion, the IOT-based financial management
system makes the financing structure of new energy companies more reasonable.
In terms of investment, it was observed that the corporate investment-to-revenue
ratio was around 80% in both 2016 and 2017. And after the introduction of the IOT-
based financial management system in 2018, the corporate investment-to-revenue
ratio steadily increased year by year. Relative to the data in 2017, the investment-to-
revenue ratio decreases by 8.74%, 22.91%, and 16.83% in 2018, 2019, and 2020,
respectively. While 2020 saw a decline in the company's revenue-to-investment ratio
due to the epidemic, the IOT-based financial management system still enabled
revenue improvement to be maintained at a high level. This is also due to the volatility
of traditional energy sources at the moment and the world's focus on new energy
technologies in the context of carbon peaking.
In terms of operations, it was observed that the percentage of corporate current
assets was as high as 88.5% in 2016, while it increased to 92.27% in 2017. In
contrast, after the introduction of the IOT-based financial management system in
2018, the percentage of corporate current assets decreases and stabilizes year by
year. Relative to the data from 2017, the investment-to-revenue ratio decreases by
6.22%, 5.48% and 6.82% for 2018, 2019 and 2020, respectively. In terms of earnings
distribution, after the introduction of the IOT-based financial management system in
2018, the company's undistributed profit ratio decreases year by year. Compared to
the data from 2017, the percentage of undistributed profit decreases by 9.69%,
18.82% and 35.39% in 2018, 2019 and 2020, respectively. This indicates that the IOT-
based financial management system has led to a more rational structure of anti-
disturbance and earnings distribution in the operation of the company, and the risk is
significantly reduced.
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Figure 2. Impact of IOT financial management system on various financial indicators of the
enterprise
4.2. THE OVERALL IMPACT OF IOT-BASED BUSINESS
DEVELOPMENT
After collecting and comprehensively evaluating data at four levels of funding,
investment, operations, and revenue distribution for pilot companies within the energy
industry from 2016-2020, we then evaluated the entire enterprise based on its
exhibition to determine the impact of the IOT-based financial management system on
the overall financial management of the enterprise. We collected the mean values of
financial management, integrated personnel management, and overall profit over the
years 2016-2020 for several pilot enterprises in Guangdong Province, and the results
are shown in Figure 3. It is observed that in terms of financial management and
integrated personnel management, the capital spent on both in 2016 and 2017
remains high under the old management system, which results in the enterprises
spending a lot of money on the management of financial and personnel aspects that
are not related to the energy industry. At the same time, the average profit of the
company was not high during the two years. Therefore, this poses a great challenge
and difficulty for the development of the company. In contrast, after the introduction of
the IOT-based financial management system in 2018, a very significant reduction in
the funds consumed for financial management and integrated personnel management
was observed. Compared to the data from 2017, the financial management costs in
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2018, 2019 and 2020 are 2.822, 4.358 and 5.501 times lower, respectively. And the
money consumed for integrated personnel management is 2.964 times, 3.012 times
and 4.004 times lower, respectively. This shows that the introduction, use and
development of the IOT-based financial management system has made the overall
management of funds more efficient and scientific, and the costs have been
significantly reduced.
Finally, in terms of overall profit averages, it is observed that the average net profit
of new energy technology companies has been steadily increasing year by year. This
indicates that the introduction, use and development of the IOT-based financial
management system has not affected the profit development of the companies, but
the cost of management has been significantly reduced. This is more conducive to the
current younger new energy technology companies to have more capital and time to
develop their own energy conversion and utilization technologies and make longer-
term investments for a low-carbon future.
Figure 3. IOT financial management system on the overall capital impact of the enterprise
5. CONCLUSION
Despite the absolute number of developments and products of enterprise
management systems and platforms, there are still relatively limited and few ways to
build a unified information and control system that can enable energy enterprise
stakeholders to assess enterprise financial management risks and propose prevention
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and control strategies. In this paper, we establish an IOT financial management
system to reduce the financial management pressure of energy enterprises and
reduce the financial risks of enterprises. At the same time, it can also facilitate the
personnel of energy companies to assess the financial management risks and
propose prevention and control strategies. We conducted a pilot experiment for
several representative energy enterprises in Guangdong Province, China. We replace
the financial management system of the target pilot energy enterprises with the IOT
financial management system proposed in this paper and count the current status of
financial risk management of each enterprise in the period of 2016-2020. The
conclusions are as follows.
1.
After the introduction of the IOT-based financial management system in 2018,
a significant increase in the percentage of non-current liabilities was observed.
Relative to the 2017 data, the percentage of current liabilities decreased by
2.96%, 7.98%, and 14.59% for 2018, 2019, and 2020, respectively. The
corporate investment-to-earnings ratio decreased by 8.74%, 22.91% as well as
16.83%, respectively.
2.
It is observed that the corporate current assets ratio was as high as 88.5% in
2016, while it increased to 92.27% in 2017. In contrast, after the introduction of
the IOT-based financial management system in 2018, the investment-to-
revenue ratio decreases by 6.22%, 5.48%, and 6.82% in 2018, 2019, and
2020, respectively. The ratio of undistributed earnings is reduced by 9.69%,
18.82%, and 35.39%, respectively. This indicates that the IOT-based financial
management system has led to a more rational structure of anti-disturbance
and revenue distribution in operations, and the risk is significantly reduced.
3.
After the introduction of the IOT-based financial management system in 2018,
a very significant reduction in the funds consumed for financial management
and integrated personnel management was observed. Compared to the data
from 2017, the financial management expenses are reduced by 2.822 times,
4.358 times and 5.501 times in 2018, 2019 and 2020, respectively. And the
money consumed for integrated personnel management is 2.964 times, 3.012
times and 4.004 times lower, respectively. This shows that the introduction,
use, and development of the IOT-based financial management system has
made the overall management of funds more efficient and scientific, and the
costs have been significantly reduced.
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