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Research article
New marketing strategy model of E-commerce enterprises in the
era of digital economy
Xiuli Ma
a
, Xue Gu
b
,
c
,
*
a
Huzhou Vocational & Technical College, Huzhou, 313000, Zhejiang, China
b
Department of Management and Law, Baicheng Normal University, Baicheng, 137000, Jilin, China
c
City Graduate School, City University of Malaysia, Kuala Lumpur, 50460, Malaysia
ARTICLE INFO
Keywords:
Electronic commerce
Enterprise marketing strategy
Digital economy
Genetic algorithm
Marketing mode
ABSTRACT
With the continuous development of technology, traditional marketing methods no longer meet
the needs of the main forces of social consumption, and people urgently need more innovative
and personalized marketing strategies. E-commerce companies must develop a comprehensive
customer-oriented marketing strategy based on big data and multi-channel to achieve their long-
term healthy development. This paper rst investigated the impact of the digital economy on e-
commerce enterprises, focused on the transformation of the digital economy on the marketing
model, expounded the development analysis of e-commerce in the digital economy era, and
described the development trend of e-commerce marketing in the digital economy era. Then, this
paper expounded the current problems faced by e-commerce enterprises, and discussed the lack of
integrity, homogeneity, large-scale marketing strategies, and the lack of analysis and application
of big data. After that, this paper put forward the marketing strategy of e-commerce enterprises in
the digital economy era, and studied it from three aspects, namely, building a reasonable product
management structure, marketing strategy based on customized marketing content, and social
media marketing strategy based on information sharing. Then this paper proposed to use genetic
algorithm to strengthen the marketing strategy of e-commerce enterprises. Finally, based on
experiments and surveys, this paper used genetic algorithms to strengthen the construction of e-
commerce enterprise marketing strategy in the digital economy, and concluded that the new e-
commerce enterprise marketing strategy was 21% more satisfactory than the traditional new e-
commerce enterprise marketing strategy. Through comparison, it can see that the integrity of the
marketing plan of the new e-commerce enterprise’s marketing strategy was 0.33 higher than that
of the traditional e-commerce enterprise’s marketing strategy, and the integrity of the promotion
strategy was 0.34 higher than that of the traditional e-commerce enterprise’s marketing strategy.
After using the new e-commerce enterprise marketing strategy, the improved management
structure was 0.29 higher than that of the traditional monitoring system, and the high quality of
products was 0.18 higher than that of the traditional system.
1. Introduction
Electronic commerce is the combination of Internet information technology and traditional ofine business activities. With the
* Corresponding author. Department of Management and Law, Baicheng Normal University, Baicheng, 137000, Jilin, China.
E-mail addresses: 2006032@huvtc.edu.cn (X. Ma), guxue6278@126.com (X. Gu).
Contents lists available at ScienceDirect
Heliyon
journal homepage: www.cell.com/heliyon
https://doi.org/10.1016/j.heliyon.2024.e29038
Received 22 November 2023; Received in revised form 22 March 2024; Accepted 28 March 2024
Heliyon 10 (2024) e29038
2
development and maturity of Internet technology, e-commerce continues to grow. Its concept, connotation and meaning evolve
gradually with the evolution of technology and actual e-commerce activities. From a historical perspective and combined with the
development of information technology, the evolution of the concept of e-commerce can provide a new perspective for observing the
development of new forms of e-commerce. In 2023, the Ministry of Commerce implemented the decisions and deployments of the Party
Central Committee and the State Council to accelerate the development of the digital economy, promote the important role of e-
commerce in restoring and expanding consumption, promoting the integration of data and reality, and deepening international
cooperation, and achieve positive results in high-quality development. With the rapid development of the digital economy, e-com-
merce enterprises have also experienced a golden age of development. Through the analysis and research of relevant industry data, it is
not difcult to nd that e-commerce business cannot be separated from a large number of consumers. E-commerce enterprises can
develop normally with enough consumers. In order to survive in the highly competitive market, e-commerce enterprises must make
full use of advanced big data analysis technology and formulate marketing strategies suitable for the development of e-commerce
enterprises. Main contribution: This article mainly focuses on the research of marketing strategies related to e-commerce enterprises
in the context of big data, and proposes corresponding improvement strategies. Objective: This article aims to promote the healthy
and long-term development of e-commerce enterprises in the context of big data through improved marketing strategies based on this
foundation.
Enterprise marketing strategies are widely used in e-commerce. This article specically introduced warehousing systems that were
particularly suitable for e-commerce retailers. It discussed appropriate systems, and identied future research needs through surveys of
relevant literature [1]. The purpose of is to introduce the results of surveys conducted in the eld of e-commerce service quality levels,
determine the standards for e-commerce service quality, and on this basis, propose the importance level of the adopted e-commerce
service quality standards [2]. The aim is to develop a consumer decision-making framework based on social business trust, concep-
tualizing social business trust from a multidimensional perspective based on social technology theory [3]. A blockchain was created to
inspect and record every transaction that occurs in an e-commerce application. Blockchain protected users’ privacy from external
personnel [4]. The impact of perceived brand leadership on satisfaction and repurchase intention on e-commerce websites was studied.
In addition, the different roles of gender and age were explored in the proposed model [5]. Scholars have developed and tested a
comprehensive conceptual framework that combines various relationships, emotional commitments, and consumer engagement, using
real-time consumer responses and software to evaluate measurement and structural models [6]. The purpose is to understand the
comprehensive impact of application identity theft protection measures on consumers’ collaborative perceptions of trust, product,
service costs, and operational performance [7]. The above studies have all covered e-commerce, but there are still some shortcomings
in enterprise marketing strategies.
Many scholars have conducted analysis and research on enterprise marketing strategies. The survey found that many enterprises
adopt green marketing strategies to enhance their corporate image and business performance [8]. The purpose is to analyze the an-
tecedents of social media adoption and their impact on marketing performance mediated by social media marketing capabilities
through a technical organizational environment framework [9]. Scholars have reviewed important developments in marketing
strategy, consumer behavior, and marketing analysis in the past, and elucidated new research areas in marketing strategy, consumer
behavior, and market analysis [10]. Research has found that digital marketing has not been widely used in the small, medium, and
micro enterprise sectors, with obstacles including lack of technical literacy and insufcient support facilities for geographical con-
ditions [11]. People believed that the business model of enterprise innovation is not only the foundation of its management, but also a
systematic description of business transparency, simplicity, and usability [12]. The main purpose is to identify key strategies and
resources that may be benecial to the implementation of SMEs [13]. The purpose is to explore the opportunities and challenges faced
by enterprises in this new digital era regarding their international marketing strategies, and to study how to re examine international
marketing practices based on these developments [14]. Nonlinear phenomena are of fundamental importance in various elds of
science, engineering, and other disciplines, as most phenomena in our world are essentially nonlinear and described by nonlinear
equations [15]. The continuous genetic algorithm is introduced as an effective solver for second-order boundary value problem sys-
tems, where a smooth solution curve is used throughout the entire evolution process of the algorithm to obtain the required node
values for unknown variables [16]. The above studies have all described enterprise marketing strategies, but there are still some
shortcomings in the research of the digital economy.
In order to study the application and construction of e-commerce enterprise marketing strategy, this paper analyzed the impact of
digital economy on e-commerce enterprises. This paper studied the transformation of digital economy to marketing mode, so as to
further deepen the reform of e-commerce enterprise marketing strategy, and improve e-commerce enterprise marketing strategy in
digital economy by using genetic algorithm. Compared with the current e-commerce enterprise marketing strategy, the e-commerce
enterprise marketing strategy constructed by genetic algorithm was more perfect.
The structural framework of this article is as follows: the second part is an introduction to the impact of the digital economy on e-
commerce enterprises. The third part describes the problems currently faced by e-commerce enterprises. The fourth part discusses the
marketing strategies of e-commerce enterprises in the digital economy era. The fth part uses genetic algorithms to strengthen the
marketing strategies of e-commerce enterprises. The sixth part is an experimental study on the marketing strategy of e-commerce
enterprises based on genetic algorithms.
X. Ma and X. Gu
Heliyon 10 (2024) e29038
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2. Impact of digital economy on E-commerce enterprises
2.1. Transformation of digital economy to marketing mode
The digital economy, as a broad concept, can be included in the scope of any economic form that directly or indirectly uses data to
guide resources and promote productivity development. At the technical level, it includes emerging technologies such as big data,
cloud computing, the Internet of Things, blockchain, articial intelligence, and 5G communication. At the application level, “new
retail” and “new manufacturing” are typical representatives. The traditional marketing model is usually limited by space.
Manufacturing companies sell products through local distributors who sell products at terminals through specic stores, which greatly
limits the ow of goods. With the high popularity of the digital economy, products can be sold in a more open form in different regions,
and e-commerce has also removed the traditional man-hour limit, allowing stores to trade with customers anytime and anywhere.
Shops often bully customers, and the weak are often forced to engage in public relations because of unequal business relations. This not
only increases the cost of consumers, but also destroys the fair and fair business environment. Consumers are difcult to nd the most
reasonable products because of information inequality, and often buy inferior products at high prices. These situations can be avoided
to some extent on the digital economy platform. These platforms are open platforms. Anyone can participate in business, provide more
choices for consumers, and greatly reduce the gray area of raw material supply. In the current business environment, traders usually
take more risks, but with the emergence of new electronic payment methods, both parties have the ability to reduce risks, thus
signicantly improving efciency and business environment.
2.2. Development of E-commerce in the era of digital economy
In recent years, with the maturity of the development of network information technology and the deepening integration of
traditional business models, e-commerce, as a product of the combination of network information technology and e-commerce, has
become an important trend of economic development in the new era. The promotion and marketing of products by enterprises is an
important means for the development of enterprises, and also the vertical expansion of traditional business transactions in the en-
terprise market. The transactions between enterprises and consumers are conducted through electronic transaction mode.
Big data is a necessary tool for the development of enterprises. With the development of e-commerce, it plays an increasingly
important role in enterprises, and has an increasing impact on the development of enterprises. With the emergence of new e-commerce
marketing strategies, integrated e-commerce marketing strategies involve manufacturing enterprises. Effective integration of con-
sumers and supply chain management has formed a system that integrates sales economic standards into the new market. Therefore, as
an important means to improve the economic efciency and productivity of enterprises in the Internet era, big data is an important
engine of economic development under the new economic conditions, as shown in Fig. 1.
Fig. 1. Analysis of the development of e-commerce in the digital economy era.
X. Ma and X. Gu
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2.3. Development trend of E-commerce marketing in the era of digital economy
In recent years, with the maturity of network information technology, the development of digital economy has achieved a great
leap, and the development of e-commerce marketing strategy in the era of digital economy also has many new trends and charac-
teristics. With the development of modern digital economy and technology, the main form of social communication is traditional
television, which is changing from radio and paper media to modern social media and other new media. In the new media era, the
development of e-commerce marketing also presents a social development trend. This is mainly manifested in the form of e-commerce
online marketing, which effectively integrates these information through various search engines, and constantly develops and
transforms them into social marketing [17]. With the development of network information technology, the popularity of smart phones
among consumers and the rapid development of mobile networks, e-commerce has also been widely used. The development of
e-commerce marketing has fully utilized the popularity of mobile networks and feature phones. It continuously innovates marketing
strategies and content to attract consumer attention, and on this basis, stimulates consumer purchasing needs by utilizing the con-
venience of software purchases.
3. Current problems faced by E-commerce enterprises
3.1. Lacking integrity
At present, the economic development is still in the stage of crazy growth. Due to the low threshold of Internet operation, a large
number of companies with mixed qualities would enter the e-commerce eld. At the same time, the formulation of laws and regu-
lations lags behind, the reality of the digital economy is difcult to monitor, and many e-commerce companies have the problem of
dishonesty. Because online advertising can be veried by a third party, the information they publish is usually very incompatible with
real-time. Although these companies are not many, they have played a key role in the destruction of a few, leading to the fact that the
actual advertisements of most companies are often suspected by consumers. The after-sales service of some enterprises is difcult to
meet the needs of consumers. The foundation of e-commerce depends largely on the efciency of logistics companies. Because the
responsibilities of logistics companies often lead to the extension of delivery time, it is difcult for consumers to communicate directly
with logistics companies when facing these problems.
3.2. Homogeneous and large-scale marketing strategy
The strong development of e-commerce companies has driven the gradual expansion of the consumer market. With the continuous
reform and development of e-commerce marketing strategies, e-commerce companies have engaged in interactive and rapid marketing
activities with consumers through online platforms. It has broken the traditional product-driven marketing model of the company, but
there are also many e-commerce companies that are not good at marketing, and the marketing strategy is homogeneous and large-
scale. The homogenization marketing strategy includes two aspects: the rst is the homogenization of marketing methods.
Following the successful marketing methods of one e-commerce company, other e-commerce companies have followed suit. Ignoring
the needs of customer groups and blindly following the trend can lead to the decline of marketing efciency and marketing failure. In
order to rapidly increase market share, e-commerce companies usually use the entire category of marketing strategies. However, while
Fig. 2. Marketing strategy of homogeneity and scale.
X. Ma and X. Gu
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blindly following the product type and scale, they ignored the characteristics of their own platforms and differentiation, leading some
e-commerce platforms to take the marketing path of scale and homogeneity, as shown in Fig. 2.
Firstly, homogenization refers to the phenomenon where products from different brands within the same category imitate each
other in terms of performance, appearance, and even marketing methods, gradually converging. The market competition behavior
based on homogenization of goods is called “homogenization competition”, which can refer to the phenomenon of various types of
information with similar types, production methods, production processes, and transmission content in a certain eld. Secondly,
marketing strategy is for enterprises to take customer needs as the starting point, obtain information on customer demand and pur-
chasing power based on experience, and the expectations of the business community, and organize various business activities in a
planned manner. The homogenization of products intensies competition among enterprises, facing limited market capacity. Enter-
prises within the cluster often compete to cut corners and produce fake products to reduce production costs and gain competitive
advantages. These behaviors will ultimately form a huge “lemon market” within the regional brand’s original production area, seri-
ously damaging the regional brand image and gradually leading to decline.
3.3. Lacking application of big data
The current e-commerce companies are too focused on expanding the market and do not clearly recognize the importance of big
data for business growth. People with big data may be at the forefront of business in the future. On the one hand, they would collect and
analyze big data and accurately predict customers’ consumption trends. By understanding the consumer psychology of customers, they
can formulate appropriate marketing strategies based on these predictions to achieve greater cost savings and product inventory
reduction. On the other hand, e-commerce companies that master big data can establish their own logistics platform, greatly reducing
the logistics delivery time and cost of products. Through big data, e-commerce platforms can predict the number of specic products in
a city in the near future. E-commerce companies can transport the products that customers need to their cities, which greatly ac-
celerates logistics and reduces logistics costs.
4. Marketing strategy of E-commerce enterprises in the era of digital economy
4.1. Establishing reasonable product operation and management structure
Establishing an appropriate product management structure for e-commerce enterprises means that they classify products based on
specic product types, fully utilize big data technology, and develop product marketing strategies to meet different consumer needs.
Due to the convenience of design management, e-commerce enterprises can optimize the design of the web structure, plan the
operation and management structure, and make it easier for consumers to choose. On the other hand, in product design, e-commerce
companies focus on how products can bring good experience to consumers and provide good consumer experience. This can improve
the product quality and make it more popular in the market, as shown in Fig. 3.
The architecture route of a product is a gradual evolution process. In the early stages of informatization, enterprises basically do not
talk about product architecture, or product architecture only exists in separate systems. The management of the product department
strictly distinguishes business lines, and business lines are relatively closed and develop independently. The principles of product
architecture are as follows:
(1) Ensure the scalability of the product architecture;
(2) The product architecture needs to be highly abstract and standardized;
Fig. 3. Construction of reasonable product management structure.
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(3) Clear boundaries need to be dened within the product architecture;
(4) The product architecture needs to consider the product matrix relationship network.
With the help of information and transaction models, a complete product architecture can be basically constructed. Both trafc
model and user model can be considered simultaneously. The core of trafc model is the closed loop of trafc, which is the processing
of increment and stock, and can serve as a logical reference for the front-end part of product architecture.
4.2. Marketing strategy based on customized marketing content
Personalized marketing content is the premise for users to accept in the marketing process. If the marketing object is not accurate,
any good marketing method can not touch the hearts of consumers. In the past, correct marketing proved to be elusive for advertisers.
Fortunately, in the network era of digital economy, using data mining and personalized marketing content is no longer a problem. The
inherent accuracy of smart phone humanization includes goods and services. It can be said that marketing content such as information
can be concentrated in one place, and the target audience of advertising can be more accurately reected on the mobile phones of
people who need advertising.
4.3. Social media marketing strategy based on information sharing
Social media marketing expands the ofine and online relationships between people through new media and social media. Users
identify products through relationships, including the ability to identify and subscribe. At present, the most common types are software
marketing and online community marketing. Powerful information sharing, due to its rich content and extensive participation, can
bring amazing marketing results to enterprises if it is successfully applied to the marketing work of enterprises. For example, e-
commerce companies can create public software platforms through advertising, turn customers into friends, and then send product
news, latest events and other relevant information to fans. Products can be sold online through user groups and circle of friends.
4.4. E-commerce enterprises carry out promotional activities
The promotion strategy refers to the efforts of e-commerce companies to improve their popularity through the activities of reducing
prices. This method transmits product information to specic consumer groups through the use of advanced communication means. At
present, consumers have many choices on the network, the scope of e-commerce enterprises is also expanding, and the competition of
e-commerce companies is becoming increasingly erce. This requires e-commerce enterprises to take appropriate promotional mea-
sures according to the characteristics of their products to realize the rapid development of e-commerce enterprises. So far, it is difcult
for e-commerce companies to formulate effective sales strategies. Faced with this situation, e-commerce enterprises should fully
integrate the characteristics of e-commerce, develop relevant network questionnaires with network data as the core, understand the
actual needs of consumers, and develop advertising strategies suitable for e-commerce enterprise positioning, as shown in Fig. 4.
Next, this article lists another several promotional activities carried out by e-commerce enterprises and explains their respective
advantages and disadvantages.
5. Price reduction
Advantages: Direct price reduction to stimulate user consumption. Ofine supermarkets often use direct price reduction strategies
Fig. 4. Promotional activities carried out by e-commerce enterprises.
X. Ma and X. Gu
Heliyon 10 (2024) e29038
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because their product prices are very transparent and the discount after price reduction is very intuitive. On the other hand, online
stores usually combine price reduction activities with other activities.
Disadvantages: decreased prots; harmful to brand image, not suitable for products with controlled prices by big brands, and
difcult to continue selling after price recovery.
6. Flash sale
The discount on ash sale products is greater, mainly focusing on low-priced items, usually including limited time ash sale, limited
quantity ash sale, etc.
Advantages: easy to attract trafc, plan single item hot selling products, ash sale product waterfall ow is very suitable for
creating hot selling products on online platforms.
Disadvantages: ash sale products usually have low prices and low prots.
7. Full discount/full item discount/full item discount
It can be divided into coupon full discount coupons/system automatic full discount coupons, and can be set to multiple levels and
levels.
Advantages: full discount coupons have become a standard feature in online promotion activities, and large discount coupons can
effectively stimulate user consumption visually and increase the average order value.
8. Full offer/full refund
Customers who consume a certain amount can receive physical goods or coupons, and can set multiple levels and levels.
Advantages: provide benets to users (or WeChat agents) and stimulate consumption without any discount (without any impact on
brand prices).
9. Genetic algorithm to strengthen the marketing strategy of E-commerce enterprises
As a part of the company’s activities, the production capacity, order quantity and production plan of the company’s decision-
making department are designed according to the number of orders to be completed and the expected sales volume. For this prob-
lem, the planned order quantity and the planned export quantity are random variables, corresponding to a certain distribution, and
their specic values are unpredictable in the test process. The production of products is order signature and unpredictable orders, and
the sales process is earlier than this part of products, which means that the production plan of products does not match the generation
of these random variables. Scholars have proposed a multi chain agricultural product transaction information blockchain application
technology, which includes agricultural product transaction information chain, user information chain, and agricultural product in-
formation chain, using the design concept of alliance chain. The agricultural product information chain provides detailed information
about agricultural products, ensuring their traceability and tamper resistance. It automatically divides transaction prots through
smart contracts, improves execution efciency, reduces transaction costs, and ultimately establishes a transparent, efcient, and
applicable blockchain architecture for agricultural product transactions [18]. The basic idea of using genetic algorithms to solve
optimization problems is to describe the problem to be solved as a global optimization problem of a certain objective function, and to
interpret the objective function to be optimized as the adaptation of the biological population to the environment, as well as the
optimization variables corresponding to individual biological populations. From the current population, it uses appropriate replica-
tion, hybridization, mutation, and selection operations to generate a new generation of population, and repeats this process until the
desired population or specic evolutionary time frame is obtained. Due to the fact that single parent genetic algorithm does not use
crossover operators, even if all individuals in the population are the same, the operation of the algorithm is not affected. This is a good
way to break free from the traditional genetic algorithm’s requirement for population diversity and solve the problem of premature
convergence in traditional genetic algorithms.
For different marketing schemes, p1ij represents the sales volume of the j plan and q1ij represents the actual sales volume of the i
plan. p2ij represents the sales volume of j actually signed intention orders, q2ij represents the actual purchase intention of the goods in i,
and the sum of the sales volume of all n marketing strategies kc is:
kc=∑
n
i=1[∑
q1i
j=1
ki(p1ij)+∑
q2i
j=1
ki(p2ij)](1)
If the nal sales volume of the marketing strategy is p3i and the prot is f, then:
f=∑
n
i=1
fi(p3i)(2)
If the production cost is h, there are:
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h=∑
n
i=1
hi(xi)(3)
If the operating expenses of marketing are w, there are:
w=∑
n
i=1
wi(p1i+p2i)(4)
p1ij represents the actual sales volume of the i th, and p2ij represents the sales volume of the actual signed intention order, namely:
p1i=∑
p1i
j=1
p1ij (5)
p2i=∑
p2i
j=1
p2ij (6)
10. Experimental investigation of E-commerce enterprise marketing strategy based on genetic algorithm
Genetic algorithm is a universal algorithm for solving search problems, which can be used for various general problems. The
common features of search algorithms are as follows:
① Firstly, form a set of candidate solutions;
② Calculate the tness of these candidate solutions based on certain adaptability conditions;
③ Preserve certain candidate solutions based on tness and discard other candidate solutions;
④ Perform certain operations on the reserved candidate solutions to generate new candidate solutions.
In genetic algorithms, the above features are combined in a special way: parallel search based on chromosome populations, se-
lection operations with guessing properties, exchange operations, and mutation operations. This special combination distinguishes
genetic algorithms from other search algorithms.
E-commerce marketing includes the methods and channels for enterprises to promote and sell their products or services on the
Internet. It involves various actions to attract potential customers, increase the number of visitors to online stores, and ultimately turn
these visitors into paying customers. In order to study the specic effect of genetic algorithm on the improvement of e-commerce
enterprises’ marketing strategy, this paper analyzes the integrity of the traditional e-commerce enterprises’ marketing plan and the
perfection of the promotion strategy. Finally, this paper compares and analyzes the integrity of the marketing plan and the perfection
of the promotion strategy after the improvement of the marketing strategy of the e-commerce enterprises by genetic algorithm. First of
all, this paper investigates and analyzes the integrity of the marketing plan and the perfection of the promotion strategy after the
improvement of the marketing strategy of three e-commerce enterprises by the genetic algorithm, and compares it with the marketing
strategy of traditional e-commerce enterprises. The three e-commerce enterprises are set as A, B and C, and the specic comparison is
shown in Table 1 (Table 1 shows the data obtained from the China E-commerce Information Database).
According to the data described in Table 1, under the traditional e-commerce enterprise marketing strategy, the integrity of A’s
marketing plan is 0.51, and the integrity of the promotion strategy is 0.49. The integrity of B’s marketing plan is 0.61, and the integrity
of the promotion strategy is 0.58. The integrity of the marketing plan of C is 0.63, and the integrity of the promotion strategy is 0.51.
After the improvement of the marketing strategy of e-commerce enterprises by genetic algorithm, the integrity of A’s marketing plan is
0.87, and the perfection of the promotion strategy is 0.88. The integrity of B’s marketing plan is 0.91, and the integrity of the pro-
motion strategy is 0.83. The integrity of the marketing plan of C is 0.96, and the integrity of the promotion strategy is 0.91. From
Table 1, it can be seen that the effectiveness of the marketing strategies of new e-commerce enterprises is much better than that of
traditional e-commerce enterprises, both in terms of the completeness of marketing plans and the improvement of promotion
strategies.
On the whole, the integrity of the marketing plan of the traditional e-commerce enterprise’s marketing strategy is 0.58, and the
integrity of the promotion strategy is 0.53. After the improvement of the marketing strategy of e-commerce enterprises by genetic
algorithm, the integrity of the marketing plan is 0.91, and the perfection of the promotion strategy is 0.87. Through comparison, it can
see that the integrity of the marketing plan of the new e-commerce enterprise’s marketing strategy is 0.33 higher than that of the
Table 1
Comparison of the effects of the marketing strategies of traditional and new e-commerce enterprises.
Marketing program integrity Promotion strategy perfection
Traditional marketing strategy New marketing strategy Traditional marketing strategy New marketing strategy
A 0.51 0.87 0.49 0.88
B 0.61 0.91 0.58 0.83
C 0.63 0.96 0.51 0.91
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traditional e-commerce enterprise’s marketing strategy, and the integrity of the promotion strategy is 0.34 higher than that of the
traditional e-commerce enterprise’s marketing strategy. The marketing strategy of e-commerce enterprises can optimize the marketing
plan and promotion strategy of e-commerce enterprises. Then this paper analyzes the transaction risk and marketing information push
of three e-commerce enterprises after the improvement of the enterprise marketing strategy by genetic algorithm. The specic
investigation results are shown in Fig. 5.
Fig. 5A shows the transaction risk under different marketing strategies, and Fig. 5B shows the marketing information push under
different marketing strategies. Under the traditional e-commerce enterprise marketing strategy, A’s transaction risk is 49.2%, and
marketing information push is 59.6%. B’s transaction risk is 53.6%, and marketing information push is 63.5%. C’s transaction risk is
42.4%, and marketing information push is 68.1%. Under the new e-commerce enterprise marketing strategy, A’s transaction risk is
12.1%, and marketing information push is 90.1%. B’s transaction risk is 9.6%, and marketing information push is 92.6%. C’s trans-
action risk is 15.6%, and marketing information push is 89.4%. On the whole, under the traditional e-commerce enterprise marketing
strategy, the transaction risk is 48.4%, and the marketing information push is 63.7%. In the new e-commerce enterprise, the trans-
action risk of marketing strategy is 12.4%, and marketing information push is 90.7%.
Through comparison, it can see that the transaction risk under the new e-commerce enterprise marketing strategy is 36.0% lower
than the traditional e-commerce enterprise marketing strategy, and the marketing information push is 27.0% higher than the tradi-
tional e-commerce enterprise marketing strategy. This paper analyzes the customer group needs of three e-commerce enterprises after
using the traditional and new e-commerce enterprise marketing strategies, and investigates the improvement of the management
structure and the high quality of products. The specic results are shown in Fig. 6.
Fig. 6A shows the improvement of operation and management structure under different marketing strategies, and Fig. 6B shows the
high quality of products under different marketing strategies. After using the traditional e-commerce enterprise marketing strategy, A’s
perfect management structure is 0.71, and the product quality is 0.81. B’s perfect operation and management structure is 0.66, and the
product quality is 0.78. C’s perfect management structure is 0.61, and the product quality is 0.76. After using the new e-commerce
enterprise marketing strategy, A’s perfect management structure is 0.95, and the product quality is 0.96. B’s perfect management
structure is 0.97, and the product quality is 0.98. C’s perfect management structure is 0.92, and the product quality is 0.94. Through
comparison, it can be seen that the improved management structure after the use of the new e-commerce enterprise marketing strategy
is 0.29 higher than that before the traditional monitoring system, and the product quality is 0.18 higher than that of the traditional
system.
In order to investigate the use of genetic algorithms to strengthen the construction of e-commerce enterprise marketing strategy in
the digital economy, this paper constructs the effect of a new e-commerce enterprise marketing strategy. This paper surveys 100
employees of an e-commerce company, applies the new e-commerce enterprise marketing strategy to enterprise marketing, and adopts
the form of questionnaire. This paper investigates the comparison of employees’ satisfaction with the marketing strategies of tradi-
tional and new e-commerce enterprises. It includes satised, average and dissatised, respectively. The specic effect is shown in
Fig. 5. Traditional and new e-commerce enterprise marketing strategy effect.
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Fig. 7.
Fig. 7A shows employees’ satisfaction with the marketing strategy of traditional e-commerce enterprises, and Fig. 7B shows em-
ployees’ satisfaction with the marketing strategy of new e-commerce enterprises. According to Fig. 7A, the satisfaction of employees
with the marketing strategies of traditional e-commerce companies is 71%, the average number of people is 18%, and the
Fig. 6. Management structure and product quality under two strategies.
Fig. 7. Comparison of employee satisfaction with traditional and new e-commerce enterprise marketing strategies.
X. Ma and X. Gu
Heliyon 10 (2024) e29038
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dissatisfaction is 11%. It can be seen from Fig. 7B that 100 employees of an e-commerce company surveyed are 92% satised with the
introduction of genetic algorithm into the marketing strategy framework of e-commerce enterprises, 6% in average, and 2% dissat-
ised with the construction of a new e-commerce enterprise marketing strategy. According to the experiment and investigation, this
paper uses genetic algorithm to strengthen the construction of e-commerce enterprise marketing strategy in the digital economy, and
constructs a new e-commerce enterprise marketing strategy with 21% higher satisfaction than the traditional new e-commerce en-
terprise marketing strategy.
11. Conclusions
Currently, how to promote their own development through effective marketing strategies has become an important issue that e-
commerce enterprises need to pay attention to in the context of big data. This article mainly studies the marketing strategy related
issues of e-commerce enterprises with big data as the background, and proposes corresponding improvement strategies. This article
aims to promote the healthy and long-term development of e-commerce enterprises in the context of big data through improved
marketing strategies based on this foundation. To sum up, in the new economic era, the marketing strategy of enterprises is very
important. The erce competition between enterprises requires enterprises to constantly innovate, change marketing strategies and
maximize market space. Therefore, every enterprise should strive to implement marketing strategies in an innovative spirit. Only by
constantly changing marketing strategies and actively adapting to the needs of economic development can enterprises stand out from
the competition. E-commerce companies are shifting from single and large-scale marketing strategies to homogeneous and diversied
marketing strategies. E-commerce companies need to establish accurate integrated marketing based on big data, customer-oriented
and multi-channel to survive and develop in the future competition. The development of genetic algorithms has led to exponential
growth in the direct to consumer personal genetic testing industry (such as 23andMe, Ancestry, Microgenes, 23Rubik’s Cube, etc.),
resulting in the formation of a vast private genetic database. The author explores the potential impact of genetic algorithms on the eld
of e-commerce. Based on the results of behavioral GA research, the author proposes to incorporate the inuence of genetic factors into
the existing theoretical research framework of e-commerce, and use this to examine the potential market applications of genetic al-
gorithms. Genetic research design can be used to test causal relationships, and consumer theory can be improved by revealing the
biological mechanisms of behavior. In the future, the author will further evaluate the moral and ethical challenges related to corporate
autonomy, privacy, and discrimination, and propose a future research agenda.
Data availability statement
Data will be made available on request from the corresponding author.
Funding
This work was supported by Excellent Project in Philosophy and Social Sciences of Huzhou City.
Project Name: Research on Platform Supply Chain Governance Measures.
Project Number: 21hzghy125.
Project Manager: Xiuli Ma.
This work was supported by Program for Innovative Research Team of Baicheng Normal University.
[Foundation Project] 2023 Jilin Provincial Education Department Scientic Research.
Project Name: The New Business Professional Education and teaching system under the background of curriculum ideological and
political exploration.
Project Number: JJKH20230026SK.
Project Manager: Xue Gu;
[Foundation Project] 2023 the research project of higher education in Jilin province,
Project Name: Research on the integration of new business professional education with the education of innovation and innovation
in the New Era,
Project Number: JGJX2023D533,
Project Manager: Xue Gu.
Ethical approval
The experiment was approved by the Academic Ethics Committee of Baicheng Normal University. Full name of ethics committee:
Academic Ethics Committee. File number: Commissioned by Huzhou Vocational & Technical College【2021】No.21.
I conrming that informed consent was obtained from all participants for my experiments.
CRediT authorship contribution statement
Xiuli Ma: Writing – original draft. Xue Gu: Writing – review & editing.
X. Ma and X. Gu
Heliyon 10 (2024) e29038
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Declaration of competing interest
The authors declare that they have no known competing nancial interests or personal relationships that could have appeared to
inuence the work reported in this paper.
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Xiuli Ma was born Wenshang, Shandong. P.R. China, in 1973. She received the Master’s degree from Zhejiang Gongshang University, P.R.
China. Now, she works in School of economic management and E-commerce, Huzhou Vocational & Technical Collegey of Education, Her
research interests include Logistics management and e-commerce supply chain management. Email: 2006032@huvtc.edu.cn
Xue Gu was born in Songyuan, Jilin.P.R. China, in 1990. She received the bachelor’s degree from Baicheng Normal University, master’s
degree from Changchun University of Science and Technology. Now, she works in Baicheng Normal University and studies in City University
of Malaysia. Her research interests include Business Management and Entrepreneurship Education. E-mail: guxue6278@126.com
X. Ma and X. Gu