1. Introduction

1.1. Digital Economy: Definition and Background

With the rapid development of information technology, the global economy is undergoing a major transformation, and the digital economy has become an important part of today's world economy. Digital economy refers to the economic activities based on digital technology through Internet platforms and digital tools. It not only includes Internet based business activities, but also involves the construction of digital infrastructure. The digital economy covers many fields, and its key components include e-commerce, big data, cloud computing, and artificial intelligence. Data, as a new factor of production, is changing the traditional mode of economic operation and thus driving economic transformation and development.

In recent years, the scale and influence of the digital economy have continued to expand, and its role in promoting global economic development has become increasingly significant. In many developed countries, the economic growth brought by the digital economy has reached unimaginable heights. The development of the digital economy is not limited to technologically advanced countries. In many developing countries, digital technology is also rapidly spreading and penetrating into various industries. Through the application of digital technology, enterprises from various countries have not only achieved efficiency improvements, but also gained a more advantageous competitive position in the global market. The globalization of the digital economy is an inevitable historical development, characterized by the acceleration of technological innovation and the transformation of market structure, which will have profound impacts on various industries [1]. Only by seizing the development trend of digital economy can countries grasp the advantages of international competition.

1.2. Traditional Economy: Concepts and Characteristics

Compared to the digital economy, the traditional economy is centered around physical assets and labor-intensive production. Traditional economy enterprises typically rely on fixed production facilities and manual labor, such as traditional manufacturing factories and physical retail stores. In this economic model, the operation of enterprises is highly dependent on physical infrastructure such as factories, warehouses, and stores, and economic activities mainly revolve around manufacturing, logistics, and retail. These enterprises have significant advantages in a stable market environment, such as establishing a stable customer base and relatively mature operational processes. Enterprises in traditional economies typically require a large amount of physical assets, such as production equipment and warehousing facilities, which require high investment and maintenance costs; In addition, the use of technology in traditional economies is relatively lagging behind, and the adoption speed of new technologies by enterprises is slow, which limits their ability to innovate and improve efficiency.

Taking the retail industry as an example, Wal Mart has achieved large-scale operations worldwide by relying on its extensive physical store network and supply chain system. These have enabled it to have a good brand awareness, stable customer groups and a relatively stable market share. Physical stores allow consumers to see the quality of products more intuitively, which is indeed something that online stores cannot achieve. However, this single entity business model also has significant limitations. Compared to e-commerce, the operating costs of physical stores are higher, including rent, employee salaries, and inventory management expenses. Moreover, due to the development of e-commerce, consumers are increasingly inclined to shop online, which puts traditional physical business models at a disadvantage compared to e-commerce giants Amazon and Alibaba. In the manufacturing industry, traditional standardized production methods do have a certain degree of efficiency. However, nowadays technology is developing rapidly and constantly innovating and iterating. Focusing solely on production efficiency often overlooks technological updates and changes in market demand, which is also where traditional manufacturing is inferior to intelligent manufacturing.

1.3. Impact of the digital economy on the traditional economy

This paper explores the impact of the digital economy on the retail and manufacturing industries through case studies. The retail industry faces changes in consumer behavior and the need to integrate online and offline channels, while the manufacturing industry relies on smart manufacturing and data-driven supply chain management to improve production efficiency and resource utilization. The research question centers on how the digital economy optimizes operations in these sectors.

Next, the paper will analyze the challenges and opportunities that the digital economy brings to these two industries. The difficulties that retail companies face in implementing omnichannel strategies, and the challenges that manufacturing companies encounter with technology upgrades and talent development in their digital transformation, will be key areas of discussion. Additionally, the paper will offer recommendations on how companies can better adapt to the changes brought by the digital economy through technological innovation, optimizing management processes, and strengthening collaboration between industry, academia, and research. Finally, the paper will summarize the impact of the digital economy on the retail and manufacturing industries and look ahead to future research directions, particularly the potential effects on other industries and trends in cross-industry digital integration.

2. Case Description

2.1. Retail Industry Cases

Yonghui Supermarket, as a leading traditional retail enterprise in China, has successfully responded to the challenges of e-commerce platforms through digital transformation.

Driven by the digital economy, Yonghui Supermarket has integrated online and offline sales models, utilizing the advantages of its fresh food supply chain to optimize inventory management through big data analysis and accurately match consumer needs. At the same time, Yonghui Supermarket has also launched its own online platform, achieving seamless integration between logistics, warehousing, and stores, improving operational efficiency and customer experience [2]. Digital technology also helps businesses optimize supply chain management, improve inventory turnover and logistics delivery efficiency. This digital model not only improves the operational efficiency of enterprises, but also accelerates the transformation of traditional retail to online models. In addition to Yonghui, other retail companies such as JD.com have also achieved intelligent and efficient operation of their supply chains through digital innovation. JD has introduced automated robots and drones in the warehousing and distribution process, achieving intelligent management of logistics and significantly improving delivery efficiency and customer satisfaction. By integrating online and offline channels, JD.com has further optimized the shopping experience for consumers [3].

2.2. Manufacturing Industry Cases

In the manufacturing industry, the digital transformation of the automotive industry also has a significant impact. Taking Tesla as an example, it has promoted the development of intelligent manufacturing through the widespread application of big data, Internet of Things, and artificial intelligence technologies. Tesla's production line has achieved high automation, not only improved production efficiency, but also continuously optimizing vehicle design and production processes through data-driven methods. Tesla's vehicles monitor their operational status in real-time through IoT technology, allowing enterprises to remotely update software and upgrade functions, enabling continuous optimization of vehicles throughout their entire lifecycle. Digital technology has helped Tesla achieve seamless integration in product research and development, manufacturing, sales, and other aspects, forming a complete digital industry chain. This digital model enables enterprises to quickly respond to market demand, optimize resource allocation, and reduce production costs, promoting the intelligent upgrading of the automotive manufacturing industry [4].

3. Analysis on the Problem

3.1. Transformation and Challenges in the Retail Industry

With the increasing digitization of consumer behavior, the traditional retail industry is facing profound transformation needs. The digital economy has not only changed the way consumers shop, but also accelerated the integration of online and offline retail enterprises. Taking Yonghui Supermarket as an example, traditional retail enterprises have achieved success in the digital age by integrating online and offline resources through big data technology and supply chain optimization. However, this transformation has brought many challenges, especially in terms of data integration and operational coordination in the implementation of omnichannel strategies. In the process of promoting digital transformation, retail enterprises must reconstruct their supply chains in order to respond to market demand faster and more efficiently, while improving inventory management efficiency [5].

Globally, another major challenge facing traditional retailers is how to remain competitive with digital natives. E-commerce giants such as JD.com and Amazon have built powerful logistics and delivery networks through the deep application of artificial intelligence and big data technology, enabling them to provide services to consumers faster and more efficiently than traditional retailers [6]. For traditional retailers, this pressure forces them not only to keep up with technological changes in digital transformation, but also to find new balance points in cost management and customer experience.

Personalized consumption demand is one of the important factors driving the transformation of the retail industry. With the rise of e-commerce platforms, consumers' demand for personalized products and services is increasing. Traditional retail enterprises must collect and analyze consumer data through digital technology to provide more accurate marketing strategies and product recommendations. This model not only enhances consumer stickiness, but also helps businesses improve sales conversion rates. However, this also means that retail enterprises need to invest a significant number of resources in data collection, analysis, and management to ensure that they can provide consumers with the best personalized experience [7].

At the same time, supply chain management in the retail industry is also facing digital challenges. Traditional supply chains typically operate in a fixed inventory model, which cannot be flexibly adjusted in rapidly changing markets. However, digital supply chain systems allow companies to adjust inventory levels based on real-time data, reducing situations of inventory surplus and shortage. For example, Yonghui Supermarket uses big data technology to accurately predict market demand, adjust inventory strategies, significantly reduce inventory backlog, improve operational efficiency, and gradually mature the enterprise in the process of digital transformation [2].

3.2. Digital Transformation and Challenges in Manufacturing Industry

Compared to the retail industry, the challenges faced by the manufacturing industry in digital transformation are more complex and far-reaching. The application of intelligent manufacturing and industrial Internet has completely changed the production mode and efficiency management of the manufacturing industry. For example, Tesla has created highly automated production lines by introducing the Internet of Things, big data, and artificial intelligence, achieving full process optimization from design to manufacturing. This not only improves production efficiency, but also reduces operating costs and significantly improves product quality [4]. However, the digital transformation of traditional manufacturing industries is not always smooth sailing, especially as traditional manufacturing enterprises face the dual dilemma of technological upgrading and talent shortage. Due to limited resources, small and medium-sized enterprises find it difficult to gain an advantage in technological competition, leading to significant pressure in the globalized market [8].

Technological upgrading is the core issue of digital transformation in the manufacturing industry. Intelligent manufacturing requires enterprises to invest a large amount of capital in updating equipment, optimizing processes, and establishing strong data analysis capabilities. However, many small and medium-sized enterprises face difficulties in achieving comprehensive technological upgrades due to funding shortages, which greatly limits their digitalization process. In addition, the organizational structure of traditional manufacturing enterprises is relatively rigid, and they often respond slowly to rapidly changing market demands. This limitation not only affects the production efficiency of enterprises, but also makes it difficult for them to cope with the constantly changing market demands in the digital economy.

In addition, talent shortage is also a key obstacle to the digital transformation of the manufacturing industry. The demand for high-quality technical talents in the digital economy era is constantly increasing, especially in fields such as data analysis, automation system operation, and intelligent manufacturing. However, many traditional manufacturing enterprises are relatively lagging in talent introduction and training, resulting in a lack of sufficient professional talent support for enterprises in promoting digital transformation [8]. Enterprises not only need to improve the technical level of existing employees through internal training, but also need to strengthen cooperation with external educational institutions and technology companies to attract more technical talents to enter the manufacturing industry.

The digitization of the supply chain in the manufacturing industry is also a major challenge in the transformation. In traditional manufacturing models, the operation of the supply chain is relatively closed, information flow is slow, and it is difficult to cope with rapid changes in the global market. By introducing digital technology, manufacturing enterprises can achieve intelligent management of their supply chain, ensuring real-time sharing and feedback of information at every stage from raw material procurement to product delivery [9]. For example, Tesla uses IoT technology to monitor every link in the supply chain in real-time, ensuring that production plans can be dynamically adjusted according to market demand. This not only improves supply chain efficiency but also reduces resource waste.

3.3. Markets in the Digital Economy

Although the digital economy has provided numerous opportunities and innovative solutions for the retail and manufacturing industries, it has also raised new issues. Especially in terms of data security, privacy protection, technological monopolies, and market failures. Firstly, data security and privacy protection have become one of the core issues faced by enterprises. As companies collect, process, and analyze a large amount of consumer data, the risk of data breaches also increases. Ensuring the legitimate use of data and protecting consumer privacy has become a key challenge for enterprises as they drive digital transformation. Data abuse may not only lead to a decrease in consumer trust, but also bring legal responsibility and ethical disputes [5].

Secondly, the widely used technological means in the digital economy, such as artificial intelligence and big data, have also led to market failures to a certain extent. The problems of information asymmetry, uneven resource allocation, and technological monopoly have exacerbated unfair competition in the market. For example, some large technology companies restrict market entry opportunities for small and medium-sized enterprises by monopolizing technology and data resources. This phenomenon weakens the innovation capability of the market and increases the difficulty of survival for small and medium-sized enterprises [9]. This monopoly phenomenon not only reduces market competitiveness but may also inhibit the innovation drive of the entire industry.

In addition, the rapid development of technology has made it difficult for small and medium-sized enterprises to keep up with the market pace, forming technological barriers. These enterprises lack sufficient funds and technological resources to carry out comprehensive technological upgrades, especially in the early stages of digital transformation, often facing significant technological investment pressure. This technological barrier not only makes it difficult for small and medium-sized enterprises to maintain competitiveness in the market, but also further exacerbates unequal competition in the market.

4. Suggestion

4.1. Suggestions for the Retail Industry

In response to the challenges faced by the retail industry, enterprises need to further integrate into the digital economy to cope with market competition and changes in consumer demand. Firstly, retail enterprises should strengthen their data analysis capabilities. Through big data technology, enterprises can better understand consumer needs and provide personalized products and services. Enterprises should actively invest in data analysis platforms, utilize intelligent technology to enhance insights into consumer behavior, and optimize sales and marketing strategies. Enterprises can invest in advanced data analysis platforms to accurately obtain consumer shopping habits, preferences, and other information, develop personalized marketing strategies, and improve sales conversion rates. For example, through intelligent algorithms and data mining, enterprises can provide accurate recommendations to customers, enhance their shopping experience and loyalty.

Secondly, retail enterprises should focus on improving customer experience. In the digital economy era, customer experience is a key factor for business success. Enterprises can provide consumers with more diversified service experiences through technological means such as artificial intelligence and virtual reality technology. The combination of online channels and offline experience is the key to improving customer satisfaction. For example, companies can enhance interaction between customers and brands and increase brand loyalty through online appointments and offline experiences.

In addition, retail enterprises should build flexible technology cooperation platforms. By collaborating with technology companies and research institutions, retail enterprises can reduce the cost of technology development and application and promote technological innovation. Enterprises should establish open technology cooperation platforms to attract external technological resources and enhance their technological advantages in digital transformation.

4.2. Suggestions for the Manufacturing Industry

To maintain competitiveness in the digital wave, the manufacturing industry needs to start from the following aspects. Firstly, enterprises should promote technological innovation and accelerate the digitalization process. The application of intelligent manufacturing and industrial Internet can significantly improve production efficiency, optimize resource allocation, and promote the comprehensive digital transformation of enterprises. Manufacturing enterprises can improve the automation level of production lines by introducing Internet of Things, industrial Internet and big data technology, thus improving production efficiency and product quality [4]. At the same time, enterprises should actively upgrade their technology to avoid being eliminated by the market due to technological backwardness.

Secondly, manufacturing enterprises should strengthen the introduction and cultivation of technical talents across departments and fields. Digital transformation cannot be achieved without the support of high-quality technical talents. Enterprises should cultivate the digital skills of existing employees through internal training and external cooperation, and enhance their abilities in data analysis, intelligent device operation, and other aspects. In addition, enterprises should actively introduce external high-tech talents, especially experts with backgrounds in big data, artificial intelligence, and the Internet of Things, to provide strong support for their technological innovation. By collaborating with universities and research institutions, enterprises can enhance their technological research and development capabilities, and promote the application of innovative achievements in production.

At the same time, manufacturing enterprises should pay attention to dynamic digital management of the supply chain. In the globalized market, enterprises need to carry out refined management of various links in the supply chain. By optimizing supply chain management, manufacturing enterprises can achieve efficient management from raw material procurement to product delivery, reducing resource waste and inventory backlog. Enterprises can also use data analysis technology to monitor every link in the supply chain in real time, ensuring the flexibility and efficiency of the supply chain, thereby enhancing their market competition.

Finally, manufacturing enterprises should strengthen cooperation with the government and industry associations and strive to obtain more resources in digital policies and financial support. By actively participating in the development of industry digital standards, enterprises can take the initiative in technological transformation and leverage government policies and financial support to reduce the costs and risks of digital transformation [10].

5. Conclusion

5.1. Summary of main findings

This study demonstrates that the digital economy has become a pivotal driver in the transformation of the retail and manufacturing sectors. In the retail industry, digital technologies have facilitated omnichannel integration, optimized supply chains, and enhanced personalized services, significantly improving both customer experience and market competitiveness. By leveraging big data analytics and intelligent platforms, retail companies are now able to better forecast consumer demand, enable targeted marketing, and boost overall operational efficiency. This digital shift has not only transformed internal business operations but also revolutionized the way consumers engage with brands.

In the manufacturing industry, the digital economy has promoted the wide application of intelligent manufacturing and industrial Internet, and promoted the innovation of production automation, resource optimization and supply chain management. Manufacturing enterprises utilizing the Internet of Things and big data technology not only improve production efficiency, but also promote the intelligent transformation of product design and production processes. At the same time, the technological and financial barriers faced by small and medium-sized enterprises in the process of digital transformation have become prominent, indicating that technological upgrading and talent introduction will become key elements for enterprises in future digital competition.

The digital economy not only brings technological innovation, but also changes the operational logic and market structure of industries, bringing new opportunities and challenges to enterprises. The future industry competition will depend on whether companies can successfully integrate digital technologies, promote innovation and collaboration, and form sustainable digital business models.

5.2. Future research directions

Although this study mainly explores the impact of the digital economy on retail and manufacturing industries, future research can further expand to more industries. Firstly, it is worth exploring the potential impact of the digital economy on other traditional industries, such as agriculture, energy, education, and healthcare. The digitalization level of these industries is relatively low, but they are gradually beginning to transition towards digitalization.

Secondly, future research can delve into the trend of cross industry digital integration. With the development of technology, the boundaries between industries are gradually blurred, and the digital integration of different fields will generate new business models and economic structures. Moreover, understanding the broader, systemic effects of digital transformation across industries is crucial to capturing the full potential of cross-industry synergies and ensuring equitable access to these innovations. The synergistic effects brought about by cross industry integration need to be further studied, which will provide enterprises with broader innovation opportunities and market potential.