Research on Sales Forecast of New Energy Vehicle:

Based on the Perspective of Government Subsidy

Ruidan He

School of Economic and Management, Shanghai Institute of Technology, Shanghai, China

h2569239765@163com

Keywords: New Energy Vehicle, Government Subsidy, System Dynamics, Sales Forecast.

Abstract: By studying the development status of the new energy vehicle (NEV) industry, establishing a system

dynamics scenario of NEV sales, using Vensim software for scenarioing and simulation, analyzing the impact

of technology innovation, infrastructure and other related variables on the NEV market sales, and simulating

the future development trend of NEVs. This paper concludes that the future sales of NEVs will keep growing,

which is mainly due to the increase of government subsidies and improvement of infrastructure. Finally, based

on the simulation results and combined with the actual situation, reasonable suggestions are made for the

future development of the NEV industry. The suggestions include: improving infrastructure construction;

enhancing the role of policy leadership and strengthening government regulation.

1 INTRODUCTION

In order to improve low-carbon transformation

capacity and create green prosperity, we should

gradually reduce our dependence on coal under the

premise of improving the clean and efficient

utilization of coal power, continuously optimize the

energy structure, increase the proportion of

renewable energy power in the terminal energy

consumption, vigorously develop new energy

technologies, increase the investment in new energy

research, and strongly support the development of

new energy vehicle (NEV) industry. The "NEV

Industry Development Plan (2021-2035)" issued by

the State Council requires the implementation of

preferential tax policies related to NEVs, financial

support for the construction of charging piles as

public facilities, and preferential policies for parking

and charging of NEVs. The country is strongly

supporting the development of the NEV industry, and

the tax incentives and basic measures related to

NEVs are being gradually improved. However,

according to the CCA, as of the end of December

2021, the number of NEVs in China was 7.84 million,

and the number of public charging piles was 1.147

million, with a vehicle-pile ratio of 6.83:1, with an

average of 7 vehicles having one charging pile, which

is still a certain distance from the goal of one vehicle

with one pile. The lack of public charging facilities

makes consumers hesitant about NEVs.

According to the development experience of

NEVs, government investment and support are

necessary to promote the development of NEVs. In

terms of policy evaluation, Ari Kokko studied the

role of national policies in the development of NEV

industry and pointed out that national technical

support and industrial policy support are important

pillars to promote the development of NEV industry

(Liu & Kokko 2012,

Hood & Margetts 1983).

Sierzchula pointed out that charging infrastructure is

more closely related to the adoption of electric

vehicles, and a good infrastructure can lead to a high

adoption rate of electric vehicles (Sierzchula et al.

2014). The results of McKinsey & Company show

that financial subsidy policies play an important role

in promoting and using NEVs. To some extent, the

level of government support affects the future

development trend of NEVs. Based on this, this paper

establishes a system dynamics model of NEV sales,

uses Vensim software for modeling and simulation,

analyzes the impact of technology innovation,

infrastructure and other related variables on NEV

market sales, simulates the future development trend

of NEVs, and provides suggestions for the future

development of the NEV industry.

748

He, R.

Research on Sales Forecast of New Energy Vehicle: Based on the Perspective of Government Subsidy.

DOI: 10.5220/0012043400003620

In Proceedings of the 4th International Conference on Economic Management and Model Engineering (ICEMME 2022), pages 748-752

ISBN: 978-989-758-636-1

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

2 METHOD AND

METHODOLOGY

The development of NEVs is influenced by a

combination of national policies, technological

innovation, infrastructure, economic situation and

other factors, while these factors interact with each

other and influence each other. System Dynamics is

a methodological approach and a combination of

qualitative and quantitative analysis of socio-

economic problems, which was first proposed by

Professor Forrester(Wang 1986). Therefore, this

paper adopts the system dynamics approach and uses

Vensim software to study the impact of national

policies, technological innovation and infrastructure

on the sales of NEVs.

The attractiveness of NEV products is influenced

by the level of technology, that is, technological

innovation is the main influencing factor for the

improvement of NEVs (Liu & Song 2013), which in

turn affects innovation capacity and ultimately acts

on the level of technology. It is worth mentioning that

government R&D investment can stimulate

enterprises' R&D enthusiasm on the one hand, but on

the other hand, it can also lead to enterprises'

dependence on government subsidies and innovation

inertia, which reduces the innovation capacity and

affects the improvement of technology level (

Cai

2022

). Consumer purchasing is influenced by many

factors, which are summarized in this paper by

product attractiveness (Zhou & Liu 2021). Product

attractiveness is mainly determined by a combination

of the level of infrastructure development (vehicle-

to-pile ratio) and the level of technology.

2.1 Feedback Loops and Cause-Effect

Loop Diagrams of Model

This paper studies the construction of a systematic

feedback between technological innovation,

infrastructure and the NEV industry, which mainly

includes the following feedback loops.

1. consumer purchasing → NEV Annual Sale →

NEV Holding → vehicle-pile ratio →NEV Ease of

Use → Product Appeal

2. Government subsidy → government R&D →

innovation capacity → technology innovation →

technical level → product appeal → consumer

purchasing → NEV Annual Sale→ NEV holding

3. government subsidy → government R&D →

Creative inertia → innovation capability →

technology innovation → technical level → product

appeal → consumer purchasing → NEV Annual Sale

→ NEV Holding

Based on this, the study constructs a causal loop

diagram between technological innovation,

infrastructure and the NEV industry, as shown in

Figure 1.

Figure1: Cause-and-effect loop of technological innovation, infrastructure and the NEV industry.

2.2 Determining System Boundaries of

Model

Based on the clarification of the problem, the system

scenario needs to establish the system behavior

boundary and the time boundary. In determining the

system behavior boundary, this paper is to study the

influence of government subsidies and infrastructure

construction on the sales of NEVs. Considering the

development of the NEV industry and the reasonable

time for the predictable development of new

Research on Sales Forecast of New Energy Vehicle: Based on the Perspective of Government Subsidy

749

technologies, the scenario simulation time is set from

2015 to 2025.

2.3 Scenario Assumptions

Due to the complexity of the evolution of the NEV

industry, not all factors can be taken into account, so

assumptions need to be established to discard

irrelevant factors and highlight the problem under

study. For the sales forecasting scenario of NEVs,

this paper will be based on the following three

assumptions.

1. consumer demand is sufficient and market

supply capacity is strong. That is, the manufacturers

of NEVs can roughly meet the purchase demand of

consumers and achieve a balance between supply and

demand in the market.

2. In the forecast time frame, China's

macroeconomic conditions are good, with no major

changes or economic policy turns at present. From a

long-term perspective, some uncertain influences

(e.g., the new crown outbreak in early 2020) will not

be taken into account.

3. Since this paper is based on a government

subsidy perspective study, only public charging stake

holdings are considered when considering charging

stake holdings. Given the availability of data and the

limited space, this paper studies the key influencing

factors and certain secondary factors (e.g.,

government investment in regulatory mechanisms)

will not be considered.

2.4 System Dynamics Flow Diagram of

Model

Based on the above causal loop diagram and the

system boundary of the scenario, the system

dynamics flow diagram of technological innovation,

infrastructure and NEV industry was constructed by

Vensim software, as shown in Figure 2.

Figure2: System dynamics flow diagram of the NEV, technology innovation and infrastructure.

The data in this simulation study were compiled

from the CAAM, CBIRI, and data from the China

Public Charging Pile Industry Research Report by

Ariadne Consulting. The formulae of the main

variables in the scenario are shown in Table 1.

Table 1: Main variable equations of the scenario.

No. Equation of variables

Unit

1 Product appeal = technical level * 0.91 + NEV Ease of Use * 0.43 dmnl

2 Creative inertia= LN ("government R&D") dmnl

3 Technical level= INTEG (technology innovation,1.02) dmnl

ICEMME 2022 - The International Conference on Economic Management and Model Engineering

750

Government subsidy=IF THEN ELSE (NEV holding<=500, NEV Annual

Sale *0.5, IF THEN ELSE (NEV holding>500:AND: NEV holding

<=1000, NEV Annual Sale *0.3, NEV Annual Sale *0.1)

million

5 NEV Holding = INTEG (NEV Annual Sale - NEV Annual Scrap,15) million units

6 NEV Annual Scrap = NEV holding * vehicle scrap rate million units

7 NEV Annual Sale = government purchasing + consumer purchasing

million units

8 Vehicle-pile ratio = NEV holding /charge pile holding

dmnl

3 SIMULATION ANALYSIS OF

THE SCENARIO

3.1 Stability Check of the Scenario

The system dynamics model of technology

innovation, infrastructure and NEV industry

constructed in this study is suitable for stability

testing and simulation analysis because the portrayal

and fitting of technology innovation, infrastructure

and NEV industry are basically in line with the actual

situation. In this paper, the simulation time is 10

years, and the initial values of NEV ownership for

models 1, 2, 3, 4 and 5 are assumed to be 50,000,

10,0000, 15,0000, 20,0000 and 250,000,

respectively. As can be seen from Figures 3 and 4,

increasing or decreasing the initial values of the

variables within 10 years, although the annual sales

and annual scrapping of NEVs do not increase at the

same rate, they still generally maintain an upward

trend, so this study is consistent with the

requirements of the stability test.

3.2 Simulation Analysis of the Scenario

The simulation study in this paper uses Vensim

software, and the model is simulated in annual steps

with a simulation period of 10 years. This paper sets

up three different combinations of government

subsidies to study the impact of government subsidies

on the sales of NEVs. The initial value of government

subsidies in scenario 1 is 3000 RMB when the

ownership of NEVs is less than 5 million, 1500 RMB

when the ownership of NEVs is more than 5 million

and less than 10 million, and 500 RMB when the

ownership of NEVs is more than 10 million,

Scenarios 2 and 3 increase the amount of government

subsidies in turn. From Figure 5, we can see that the

higher the government subsidy, the higher the annual

sales of NEVs, therefore, the government should

increase the amount of government subsidy.

Figure 3: Annual sales trend of NEVs. Figure 4: Trend of annual scrapping volume of NEVs.

Research on Sales Forecast of New Energy Vehicle: Based on the Perspective of Government Subsidy

751

Figure 5: Trends in annual sales of NEVs when changing

government subsidies.

Figure 6: Trends in annual sales of NEVs when improving

infrastructure.

In this paper, three different charging pile

retention table functions are set to study the impact of

infrastructure construction on NEV sales. On the

basis of the original scenario, scenario 2 increases the

retention of charging piles, and scenario 3 is to

increase the retention of charging piles on the basis

of scenario 2. From Figure 6, we can see that with the

increase of the retention of charging piles, the

vehicle-pile ratio is decreasing and the annual sales

of NEVs are increasing.

4 CONCLUSIONS

First, although the development of an industry cannot

rely on government support, the current lack of

technology and infrastructure of NEVs, if the

government increases the subsidies for NEVs, it will

increase consumer demand for NEVs, thus

promoting the increase of NEV sales. It is suggested

that the price authorities of the local governments

promoting NEVs can formulate reasonable charging

policies according to the actual situation, so that the

cost of using NEVs is lower than that of traditional

vehicles, thus increasing consumers' willingness to

buy NEVs.

Secondly, from the simulation analysis, it can be

seen that the sales of NEVs increase as the number of

charging piles increases, i.e., the infrastructure

continues to improve. Therefore, in terms of service

platform, it is suggested that the government should

make use of the existing technology to actively

develop the "Internet+Charging Infrastructure"

platform to help the owners of NEVs to achieve

charging navigation and fee settlement, so that

consumers can feel the convenience of using NEVs

and further increase the sales of NEVs.

ACKNOWLEDGMENTS

The researchers would like to express their gratitude

to the anonymous reviewers for their efforts to

improve the quality of this paper.

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