(Article In Press)Analysis of digital transformation path of small and medium-sized (https://doi.org/10.63386/619084)

Fei Wang *

School of Accounting, Shandong Youth University of Political Science, Jinan, 250103, Shandong, China

Email: wf_sdufe@163.com

enterprises based on new quality productivity

Abstract: The new quality productivity, characterized by innovation-driven growth, enhanced efficiency across all factors of production, and sustainability, provides technical support and a development model for the transformation of small and medium-sized enterprises (SMEs). However, SMEs face challenges such as insufficient internal motivation for transformation and the need for tailored strategies. Research indicates that the transformation path based on new quality productivity should focus on innovation-driven technological advancements, changes in management models, talent incentives and organizational capacity building, and policy support and guarantees. This approach aims to systematically enhance the digitalization level of SMEs, thereby facilitating their high-quality development in the wave of new quality productivity.

Key words: new quality productivity; small and medium-sized enterprises; digital transformation

 foreword

As China’s modernization and the digital intelligence era advance, small and medium-sized enterprises (SMEs), which are crucial for economic growth and job creation, must urgently achieve digital transformation to secure sustainable development. With the rapid advancement of the new technological and industrial revolutions, the innovation-driven approach of digital technology helps SMEs overcome technical barriers, foster disruptive and cutting-edge technologies, develop intelligent production models, and enhance their R&D capabilities. However, SMEs face challenges in financing, difficulty in implementation, and a weak foundation for digital transformation. The technological innovations driven by new productive forces offer opportunities for companies to break through bottlenecks, and exploring suitable transformation paths is essential for revitalizing SMEs and promoting industrial upgrades.

First, the basic characteristics of new productive forces

(1) Innovation-driven

As a new form of productive forces leading economic development, innovation-driven is the core and key characteristic of new productive forces. In the development of these new productive forces, scientific and technological innovation has become the primary driving force, from fundamental technology research and development to application innovation, spanning production, management, and service. For example, in the digital domain, the continuous iteration of artificial intelligence algorithms and breakthroughs in big data analysis have driven enterprises to shift their production models from traditional experience-based to data-driven. In terms of product innovation, companies can develop more market-demand-driven and competitive products by leveraging new technologies, meeting consumers’ increasingly diverse and personalized needs. This innovation is not confined to a single technology or product but exhibits a multi-field, multi-level integration trend. Technological innovation, business model innovation, and management innovation are interwoven and progress together, collectively driving industrial upgrading and the deep adjustment of the economic structure[1].

(2) Total factor productivity increased

The improvement in the total factor productivity of new productive forces is reflected in the deep optimization and collaborative transformation of all production factors. Empowered by digital and intelligent technologies, the labor force is no longer limited to traditional physical strength and simple skills but has evolved into a knowledge-based and technology-driven workforce. Workers can use digital tools to complete tasks more efficiently, leading to a significant boost in labor productivity. Capital, through precise matching by digital technology, reduces the risk of resource misallocation and enhances the efficiency and return on investment of capital. Land and equipment, among other tangible resources, are managed intelligently through the Internet of Things (IoT) and big data, avoiding idleness and waste and improving utilization rates. Meanwhile, data, as a new type of production factor, is deeply mined and applied throughout the R&D, production, and sales processes, integrating with other factors to drive business process reengineering and innovation in business models. This approach breaks the traditional limitation of diminishing marginal returns on production factors, creating a synergistic amplification effect among factors, thereby promoting a comprehensive improvement in the efficiency of enterprises in production, management, and service.

(3) Sustainability

The sustainable nature of new productive forces is a core attribute shaped by the global consensus on green development and the wave of technological innovation. Conceptually, it moves away from the traditional model of high resource consumption and environmental pollution for economic growth, integrating green, circular, and low-carbon development into every aspect of production. Practically, it leverages clean energy technologies, energy-saving and environmental protection processes, and digital management methods to achieve efficient resource recycling and pollutant reduction. By optimizing supply chains through big data analysis, it reduces resource waste in intermediate stages and lowers logistics carbon emissions. Additionally, the sustainability of new productive forces is also reflected in the promotion of a green and low-carbon industrial structure, fostering the development of emerging industries such as energy conservation, environmental protection, and new energy, and nurturing new economic growth points.

Second, the role of new quality productivity in the digital transformation of small and medium-sized enterprises

(1) Technological innovation promotes digital transformation

In the context of new quality productivity, technological innovation injects core momentum into the digital transformation of small and medium-sized enterprises (SMEs) from multiple dimensions. In terms of products, the deep integration of technologies such as big data, artificial intelligence, and the Internet of Things (IoT) drives product development towards smarter and more personalized directions. Companies can uncover potential needs through user behavior data, leading to iterative upgrades and innovative designs, making their products feature digital capabilities like data collection and intelligent interaction. In services, cloud computing and mobile internet technologies break down time and space barriers, enabling companies to build online service platforms. By optimizing digital service processes, these platforms enhance customer experience, achieve real-time and precise service responses, and use data analysis to predict service demands, allowing for early planning of service content. In the production process, the application of industrial internet and automation technologies promotes the interconnectivity of production equipment and the digital transformation of production processes, enabling real-time monitoring and intelligent control of production parameters. This improves production efficiency and quality stability while reducing errors and costs caused by manual intervention. The digital penetration of technological innovation in product, service, and production not only redefines the core competitiveness of enterprises but also provides solid technical support and innovative pathways for SMEs to achieve digital transformation in the new quality productivity environment[2].

(2) Improve the effectiveness of enterprise operation and management

The new quality productivity has significantly enhanced the management and operational efficiency of small and medium-sized enterprises (SMEs). According to survey data (see Figure 1), over 64.35% of SMEs believe it can greatly improve their management and operational levels, 12.93% think it can slightly improve them, 20.82% recognize its decisive role, and only 1.89% feel it is entirely unhelpful. This improvement is due to the reshaping of management models by digital technology under the new quality productivity. Through big data analysis, companies can gain precise insights into market demand and optimize resource allocation. Intelligent management systems make process approvals and production scheduling more efficient, breaking down departmental barriers to achieve collaborative operations. Digital platforms enable decision-makers to access real-time business data, supporting scientific decision-making and enhancing the management and operational efficiency of SMEs from multiple dimensions, thus becoming a key force in optimizing internal operations during the transformation process.

(Figure 1: The digital transformation of SME tasks to improve the effectiveness of enterprise management)

(3) Talent incentive and organizational capacity building

In the digital transformation of small and medium-sized enterprises (SMEs), new quality productivity uniquely empowers talent incentives and organizational capacity building, driving continuous digital innovation. From the perspective of talent incentives, the digital business scenarios created by new quality productivity provide a broad platform for employees to showcase their technical skills. Companies can establish special rewards for digital projects, such as offering equity or performance incentives to employees who excel in big data analysis and intelligent system maintenance, thereby stimulating their enthusiasm for exploring digital innovation. Additionally, the flexible work models under new quality productivity align with young talents’ desire for autonomy, serving as an implicit incentive. In terms of organizational capacity building, new quality productivity requires companies to build digital learning organizations. By utilizing online training platforms and industry technology exchange salons, companies can ensure that employees continuously engage with cutting-edge technologies like artificial intelligence and the Internet of Things (IoT), thereby enhancing their digital skills. The organizational structure is also evolving towards a flatter and more agile model, breaking down departmental barriers to promote efficient collaboration among R&D, operations, and marketing teams around digital innovation, enabling companies to swiftly respond to market demands and launch new digital products and services[3].

Third, the challenges faced by SMEs in digital transformation

(1) There are insufficient internal impetus for transformation

Small and medium-sized enterprises (SMEs) often face challenges such as limited resources and weak risk resistance. In terms of digital investment, they lack the courage and capability to match those of large enterprises. Particularly in the industrial sector, SMEs have a natural deficiency in digital capabilities, lagging behind in R&D infrastructure, personnel reserves, technological accumulation, and investment intensity. Data shows that while the average office network coverage rate for SMEs has reached 89%, only 35% of devices are connected to the internet, leaving many devices like ‘deaf and mute’ devices, with a very weak foundation for digitalization. Relying solely on their own efforts, SMEs find it difficult to identify the right direction for transformation, and often fail to achieve significant results before facing numerous difficulties that make it hard to continue. Therefore, the digital transformation of SMEs particularly requires external guidance and the overall drive from the industrial chain. To address the actual needs of SMEs, targeted, comprehensive, and inclusive transformation solutions should be developed, enabling companies to clearly see the path to transformation, tangibly experience the results, and gain confidence in the transformation process, steadily advancing their digital upgrade.

(2) More differentiated policies are needed for transformation and benchmarking

Not all small and medium-sized enterprises (SMEs) need to undergo digital transformation, and the paths to digital transformation are not uniform or universal. By categorizing SMEs based on industry, sector, scale, region, or traditional versus emerging industries, targeted research and analysis can be conducted to accurately identify enterprises with genuine digital transformation needs. Policies should then be tailored to the specific characteristics of these enterprises, such as their type, sector, and scale, to promote targeted transformation. From an industry perspective, discrete manufacturing should focus on enhancing digital applications in areas like energy management and equipment maintenance. Process manufacturing should concentrate on optimizing processes, integrating systems, and improving customer service, thereby strengthening the integration of digital technology. For individual enterprises, leading chain enterprises and major players should strive for innovation in technology and business models to set benchmarks for digital transformation within their industries. In contrast, a wide range of SMEs should focus on niche markets, leveraging new information technologies to enhance product quality and production efficiency, which should be their primary focus for digital transformation[4].

Fourth, the digital transformation path of small and medium-sized enterprises based on new quality productivity

(1) Technology innovation driven path

The digital transformation of small and medium-sized enterprises (SMEs) based on new productive forces is significantly supported by the path driven by technological innovation. SMEs should actively adopt advanced digital technologies such as big data, cloud computing, artificial intelligence, and the Internet of Things (IoT). By leveraging big data to extract value from internal and external data, they can assist in decision-making. Cloud computing enables them to flexibly access resources and reduce IT costs. Artificial intelligence optimizes production and service processes, while IoT facilitates device interconnection and data collection. Additionally, SMEs should enhance their R&D and innovation capabilities by either building their own teams or collaborating with industry, academia, and research institutions. They should focus on solving key business challenges and developing proprietary technology products to innovate and adapt to market needs, thereby increasing product value. Furthermore, they should promote the integration and application of technologies to leverage synergies, such as combining big data and AI for precise marketing and intelligent decision-making, and integrating IoT with blockchain to enhance supply chain transparency and security. This creates new business models and scenarios, supporting the deepening of transformation. As shown in Table 1, various technologies work together in different application scenarios, laying a solid technical foundation for the digital transformation of SMEs.

(See Table 1 for the role of each technology in different application scenarios)

(2) Path of management mode reform

In the context of new productive forces, the digital transformation of small and medium-sized enterprises (SMEs) hinges on a profound transformation in management models. The primary task is to construct a digital organizational structure. Companies need to break away from traditional hierarchical structures by reducing management levels, establishing a digital transformation leadership group, and forming cross-departmental project teams. These measures aim to promote efficient information flow and enhance organizational collaboration, thereby meeting the agile response needs of the digital age. Optimizing business processes involves using digital technology to thoroughly review core areas such as procurement, production, and sales. By leveraging process management software, companies can achieve process automation and standardization, eliminate redundant steps, improve operational efficiency, and reduce management costs. Establishing a digital decision-making mechanism aims to leverage big data analysis and visualization tools to transform internal and external data into decision-making support. This shift moves the company from an experience-driven to a data-driven scientific decision-making model, enabling managers to make informed decisions based on precise market insights and operational analysis. These three elements complement each other: a digital organizational structure provides the necessary organizational foundation for optimizing business processes and making digital decisions. Optimized business processes generate higher-quality data to support decision-making, while scientific decisions further guide adjustments in organizational structure and improvements in business processes, collectively forming the management cornerstone of SME digital transformation[5].

(3) Precise policy implementation and demonstration guidance: building a transformation promotion system

The digital transformation of small and medium-sized enterprises (SMEs) based on new productive forces should focus on precise policy implementation to establish a systematic advancement framework. First, through comprehensive research, identify the SMEs that need transformation, adhering to the principle of ‘coming from and serving SMEs.’ Use an accessible language system to design questionnaires to ensure that companies can clearly report their current level of digitalization. Simultaneously, conduct on-site research in industrial parks and clusters to accurately identify the pain points and needs of enterprises. Combine this with cross-analysis based on industry, region, and scale to pinpoint target enterprises. On this basis, systematically evaluate and compile a list of ‘pain point arrays,’ extracting the necessary resources for transformation from both vertical industry perspectives and horizontal production and operation aspects. Use scenario-based and diagrammatic methods to promote industrial chain collaboration, building a ‘pain point matrix’ that covers various industries and stages, and clearly defining the roadmap for digital transformation.

Furthermore, by focusing on scenario-based applications to establish a ‘solution set’ module, we aim to develop standardized and modular transformation solutions for the ‘pain point array.’ This involves using ‘small, fast, light, and accurate’ tool products to build a solution resource pool, enabling enterprises to select solutions as needed, thus facilitating a ‘building-block’ transformation. Additionally, leveraging the empowering role of industrial internet platforms, we promote cross-industry and cross-domain platforms to reduce enterprise transformation costs and attract high-quality service providers. Moreover, we enhance exemplary leadership by creating ‘model rooms’ benchmarks in industrial parks where enterprises cluster. Through categorized diagnosis and supply-demand matching, we aim to create model parks, cultivate transformation benchmarks, and form replicable and promotable experience models, guiding small and medium-sized enterprises (SMEs) to ‘look at the sample and learn from it,’ thereby building a healthy digital transformation ecosystem. Survey data shows that over 60% of enterprises (64.35%) believe that digital transformation can significantly enhance their management and operational levels, with 20.82% viewing it as decisive. This clearly demonstrates the positive expectations of SMEs for digital transformation and underscores the necessity and urgency of precise policy implementation and exemplary leadership strategies.

 epilogue

In summary, the digital transformation of small and medium-sized enterprises (SMEs) is a long and challenging journey. As new productive forces advance and their applications become more widespread, they are expected to create new application scenarios and opportunities for enterprise development. SMEs in our country should actively seize these opportunities, steadily advance on the path of digital transformation, and continuously move forward.

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