Can the Digital Economy Enhance the Export Competitiveness of Agricultural Products? — An Empirical Analysis Based on Panel Data from 30 Chinese Provinces

1. Introduction

As the new generation of information technology revolution—represented by big data, artificial intelligence, and the Internet of Things—sweeps across the globe, the digital economy is reshaping the landscape and trajectory of the world economy, becoming a core engine driving global economic recovery and growth [1]. In recent years, China has attached great importance to the enabling role of the digital economy in agriculture, successively issuing guiding documents such as the Strategic Outline for the Development of Digital Villages and the Digital Rural Agricultural Development Plan (2022–2025). Against this backdrop, China’s agricultural economy has achieved leapfrog development. However, according to data published in the China Agricultural Products Import and Export Annual Statistical Report, China’s agricultural product imports reached as high as USD 215.16 billion in 2024, while exports amounted to only USD 103.01 billion, resulting in a trade deficit of USD 112.15 billion—nearly double that of 2018. This indicates that China’s agricultural products have a high degree of external dependence, and the prospects for export trade and international competitiveness remain far from optimistic. Moreover, as modern agricultural production transitions from a phase prioritizing output to one prioritizing quality, people have placed higher demands on the quality of agricultural products. The contradiction between the traditional low-value-added agricultural production structure and the international consumer market has become increasingly prominent [2], severely hindering the realization of China’s strategic goal of transforming from a “large trading nation” to a “strong trading nation.” Therefore, how to harness the disruptive force of the digital economy to enable the high-quality development of agricultural product exports—and to solve the long-standing problems of low value addition, information asymmetry, and tightening environmental constraints, thereby building sustained and stable international competitive advantages—has become a major issue of both theoretical value and practical significance.

2. Literature Review

2.1. Research on the Digital Economy

Since Tapscott (1996) [3] introduced the concept of the “digital economy,” its core has consistently revolved around the restructuring of information generation, transmission, and processing methods through digital forms, aiming to enhance efficiency and reduce transaction costs (Ren and He, 2022) [4]. The digital economy is essentially a structural transformation resulting from the deep embedding of digital technologies into various sectors of the national economy, manifesting as a new economic form characterized by digital infrastructure as the foundation, digital platforms as the carrier, and data elements as the core driving force (Xu and Zhang, 2020) [5]. The G20 Digital Economy Development and Cooperation Initiative identifies digitized knowledge and information as key factors of production, a definition that has been widely adopted.

Due to differences in statistical calibers and the virtuality and high permeability of the digital economy (Wen et al., 2019) [6], there is no unified methodology for its measurement, and it faces technical constraints. Existing research primarily follows two paradigms: calculating value added based on national economic accounting, and constructing multi-dimensional indicator systems for comprehensive evaluation. Domestic studies predominantly adopt the comprehensive index method, such as Guan et al. (2020) constructing a provincial-level evaluation system [7]; the Digital Financial Inclusion Index (Guo et al., 2020) is also widely used [8]. Indicator weighting generally employs the entropy method or principal component analysis (Zhang and Ye, 2017) [9]. This paper, referencing existing studies and considering the specific implementation pathways of agricultural digitization, constructs an indicator system from three dimensions: digital infrastructure, digital industrialization, and industrial digitization.

2.2. Research on the Export Competitiveness of Agricultural Products

The measurement methods for the export competitiveness of agricultural products mainly include the Diamond Model, the Constant Market Share Model, and comprehensive evaluation indicator systems. International market share, Revealed Comparative Advantage index, and Trade Competitiveness index are widely adopted (Pan et al., 2021) [10]. In terms of measurement results, Yu et al. (2016) found that China’s exports to South Asia are at a disadvantage [11]; Yang and Tian (2022), through a comparison among China, Japan, and South Korea, found that China’s exports are primarily low- and medium-technology products [12]; Shuai et al. (2003) pointed out that while exports are growing, competitiveness is weakening [13]; in terms of product categories, vegetables and fruits outperform grains (Mao and Feng, 2007) [14]. Regarding influencing factors, the marginal contribution of traditional factors is diminishing, while the enabling effects of modern factors such as technology, information, and data are becoming prominent (Wu et al., 2023) [15]. Trade policy adjustments exert significant impacts (Narayan and Bhattacharya, 2019) [16], and technological progress is a key pathway (Li and Ding, 2016) [17]. Although it may increase production costs in the short term, it has a significant positive promoting effect in the long run (Zhang and Hu, 2013) [18]. Upon reviewing the relevant literature, it is evident that existing studies primarily analyze the impact mechanisms of agricultural product exports through their constituent elements, lacking research that incorporates the digital economy, influencing factors, and conditional factors into a unified analytical framework.

2.3. Research on the Impact of the Digital Economy on the Export Competitiveness of Agricultural Products

Existing studies have focused on the promoting role of digital tools in agricultural trade. Fan (2020) found that Internet popularization can shorten customs clearance time and reduce costs [19]; Tang and Li (2023) found that digital trade platforms can generate positive incentives [20]; Carlos Arnade (2017) found that digital platforms can reduce fixed entry costs for exports [21]; Qi et al. (2023) found that networked sales platforms can enhance production and sales efficiency [22]. However, most of these studies analyze the digital economy as a whole variable, with fewer conducting differentiated internal structural tests. In terms of transmission pathways, Zhu et al. (2019) confirmed that informatization levels have a positive impact on agricultural total factor productivity [23]; Ma et al. (2019) confirmed that digital platforms can reduce agricultural product transaction costs [24]; Bai and Huang (2021) argued that digital platforms can generate quality premiums for agricultural products [25].

Although the existing literature on the digital economy enabling agricultural product exports provides valuable insights, certain limitations remain: a lack of research incorporating the digital economy, mediation mechanisms, and threshold effects into a unified framework; and insufficient systematic testing of regional differences and conditional factors. Future research needs to integrate threshold effect models with regional heterogeneity analysis to deeply reveal the differentiated characteristics and threshold conditions of the digital economy in enabling the export competitiveness of agricultural products.

A review of the existing literature reveals that previous studies have left room for further exploration in the following aspects: (1) Most studies have focused on the linear association between the digital economy and agricultural trade, with few embedding it within a unified analytical framework of “influencing factors—transmission pathways—boundary conditions” to examine its indirect mechanisms and nonlinear characteristics. (2) Discussions on regional heterogeneity have largely been confined to mean comparisons across the eastern, central, and western macro-regions, lacking a nuanced examination of structural dimensions in agricultural production, such as grain functional zones. (3) Constrained by the narrowness of research perspectives, few studies have integrated mediation mechanisms and threshold effects into a coherent empirical framework, making it difficult to comprehensively uncover the “black box” of how the digital economy is associated with agricultural export competitiveness.

Accordingly, the marginal contributions of this paper are threefold. First, we construct a multiple-mediation framework of “digital economy → (industrial structure upgrading/technological innovation/labor transfer) → agricultural export competitiveness,” thereby opening the “black box” of the transmission pathways through which the digital economy is associated with export competitiveness. Second, we introduce trade openness as a threshold variable to reveal the “nonlinear leap” in this association as external market conditions evolve. Third, we conduct heterogeneity analyses from both geographic regional and grain functional zone perspectives, providing more granular empirical evidence for differentiated policy design. These three contributions together constitute the incremental value of this paper relative to the existing literature, helping to deepen the systematic understanding of the relationship between the digital economy and agricultural trade, while offering an extensible analytical framework for future research.

3. Theoretical Analysis and Research Hypotheses

3.1. The Direct Impact of the Digital Economy on the Export Competitiveness of Agricultural Products

Against the backdrop of the rapid penetration of agricultural digitization, the digital economy has become an endogenous driving force for rural economic development. Its direct impact on the export competitiveness of agricultural products is primarily reflected in the following three aspects: (1) In agricultural production, the digital economy can promote the intelligent, intensive, and precise development of traditional agriculture [26]. Internet of Things technologies, characterized by information perception, can accurately and promptly collect agricultural production data, enabling farmers to extract effective information from production data and achieve precise regulation of agricultural production. Meanwhile, the digital economy enhances the level of agricultural mechanization and automation, greatly improving production efficiency, reducing labor intensity and production costs, and ensuring the stability and consistency of agricultural product quality. (2) In agricultural capital circulation, the digital economy effectively alleviates the difficulties of costly and inaccessible financing faced by agricultural production through inclusive finance, mobile payments, and online credit. This enables agricultural enterprises to invest in advanced technologies, equipment, and high-quality inputs, breaking through capital constraints and avoiding agricultural cyclical problems, thereby providing the necessary financial support for enhancing the export competitiveness of agricultural products [27]. (3) In agricultural product export circulation, the digital economy breaks through traditional temporal and spatial constraints, enabling exporting enterprises to directly reach global consumers and realize a series of trade processes such as online precision marketing, trade negotiations, contract signing, export customs declaration, and inspection and quarantine. Simultaneously, the development of the digital economy enhances market transparency, facilitating farmers and agricultural exporting enterprises to adjust production strategies in a timely manner, changing their status as “price takers” and enhancing their bargaining power in factor and product markets, thereby improving the export competitiveness of agricultural products.

Furthermore, the enhancing effect of the digital economy on the export competitiveness of agricultural products may exhibit heterogeneity. First, provinces (municipalities) in different geographical locations differ in terms of policy support and resource allocation. The eastern and central regions tend to receive more policy support and resource allocation, helping them establish more comprehensive infrastructure and service systems in the digital economy field, thereby enhancing the quality and quantity of agricultural products. In contrast, the western region may be at a disadvantage in resource acquisition, facing issues such as digital technology monopolies, imperfect infrastructure, and information trade barriers. However, it may also exhibit unique advantages in agricultural production, operation, and circulation due to shorter decision-making chains and more flexible policy implementation [28]. Second, different provinces (municipalities) differ in terms of economic development levels and agricultural production modes. Major grain-producing areas typically possess abundant cultivated land resources, comprehensive infrastructure, and mature agricultural production systems, and also frequently benefit from key national policy support, further promoting the enhancing effect of the digital economy on the export competitiveness of agricultural products. Non-major grain-producing areas, constrained by geographical location and other factors, are at a disadvantage in terms of production scale, industrial structure, and product quality [29]. Based on this, this paper proposes the following hypothesis:

H1.

The digital economy can enhance the export competitiveness of agricultural products, and this enhancing effect exhibits regional heterogeneity.

3.2. Transmission Mechanisms of the Digital Economy’s Impact on the Export Competitiveness of Agricultural Products

The digital economy can indirectly enhance the export competitiveness of agricultural products through three pathways: upgrading of the agricultural industrial structure, agricultural technological innovation, and agricultural labor transfer.

First, there is a positive synergistic relationship with the upgrading of agricultural industrial structure. The digital economy enhances the efficiency of information allocation, strengthens the market’s regulatory capacity over agricultural factors, alleviates information gaps between producers and consumers, reduces factor misallocation, and promotes the coordinated development of various sub-sectors within agriculture, laying the foundation for the rationalization of the industrial structure. Meanwhile, the deep application of technologies such as the Internet of Things and big data drives the entire agricultural industry chain toward digital and intelligent evolution, breaks down traditional industrial barriers, fosters the development of new business forms, and promotes the upgrading of agriculture toward high value addition. The rationalization and upgrading of the industrial structure jointly provide solid support for the export competitiveness of agricultural products.

Second, there is a statistically positive association with the enhancement of agricultural technological innovation. The digital economy reduces the costs of information acquisition and transactions for technological innovation, enabling innovation entities to more conveniently access cutting-edge technologies and market dynamics. Digital village construction enhances the digital literacy of agricultural practitioners and promotes the implementation and transformation of technological innovation outcomes. Technological innovation, on the one hand, enhances the level of agricultural mechanization, automation, and intelligence, strengthens the synergy among various industries, and promotes the evolution of agricultural product exports toward higher quality; on the other hand, it extends the industrial chain, promotes the transformation of agricultural products toward deep processing and high value addition, and significantly enhances their international market competitiveness.

Third, there is a statistically positive association with the expansion of agricultural labor transfer. Digital technologies break down information barriers in the labor market and reduce job search costs. Flexible employment opportunities provided by Internet platforms accelerate the transfer of agricultural labor to non-agricultural sectors. Meanwhile, new business forms fostered by the digital economy create abundant employment demand, promote the optimal allocation of production factors, and enhance agricultural production efficiency. The income growth effect brought by labor transfer, through the income elasticity mechanism, stimulates the upgrading of agricultural product consumption, indirectly promoting the evolution of the agricultural industrial structure toward high value addition and enhancing export competitiveness.

In summary, this paper proposes hypothesis H2: The digital economy indirectly enhances the export competitiveness of agricultural products by promoting the upgrading of the agricultural industrial structure, stimulating agricultural technological innovation, and facilitating labor transfer. Based on this, this paper proposes the following hypothesis:

H2.

The digital economy enhances the export competitiveness of agricultural products by promoting the upgrading of the agricultural industrial structure, stimulating agricultural technological innovation, and facilitating labor transfer.

3.3. Nonlinear Impact of the Digital Economy on the Export Competitiveness of Agricultural Products

The improvement of China’s agricultural product export competitiveness is not only related to the level of digital economy development but