数字乡村政策、劳动力就业黏性与土地利用效率——基于中国家庭追踪调查（CFPS）的实证

1. Introduction

Addressing the constraints that hinder high-quality and sufficient employment among rural labor, ensuring stable employment for rural workers, and assessing the actual effects of new rural development policies in the digital era are critical for advancing rural revitalization and sustaining long-term national development. However, against the backdrop of rapid urbanization and industrialization, rural China is experiencing a substantial outflow of labor, particularly among young workers. The resulting economic consequences include not only an aging rural population, abandoned farmland, and the hollowing out of rural industries [1,2,3], but also, more fundamentally, a systemic weakening of RLFS. Conceptually, RLFS refers to the employment pattern of working-age individuals whose household registration or primary workplace is located in rural areas, characterized by low mobility and high employment stability driven by subjective preferences or the specificity of human capital. At the individual level, RLFS manifests as sustained and stable employment intentions or long, uninterrupted employment spells. In China’s dual urban–rural structure, RLFS is a key factor in maintaining stable employment relationships and is an important indicator of rural employment quality and the degree of integration between rural and urban labor markets. Higher RLFS implies that rural regions can effectively retain labor and sustain a stable local labor market; conversely, weakened RLFS signals persistent labor outflow and declining vitality in rural areas. Traditionally, the rural labor supply has relied on small-scale social networks rooted in local attachment or has been constrained by limited employment options [4,5]. These conditions generate substantial labor market mismatches, making it difficult for rural workers to form stable and long-term employment intentions. On the one hand, such distortions prevent rural labor from fully realizing its factor value; on the other hand, the rising frequency and risk of job switching undermine the healthy functioning of the labor market. Therefore, alleviating labor market distortions faced by rural workers, fostering stable employment intentions, and enhancing RLFS become one of the key issues in promoting rural development. Furthermore, as the stability of rural labor improves, whether digital rural development can effectively raise land resource utilization efficiency and activate regional factor vitality also constitutes urgent tasks for advancing rural revitalization and ensuring employment stability and sustained economic development.

The implementation of the digital rural development strategy offers a new opportunity to address these challenges. It is noteworthy that digital rural development is not merely the application of information tools but represents a profound transformation involving the restructuring of production relations and factor allocation mechanisms. Through the enhancement of digital infrastructure, the introduction of data as a factor, and the comprehensive empowerment provided by digital technologies, digital rural development profoundly affects rural economic structures, governance systems, and public service provisions [6,7], thereby creating new external conditions for the rural labor market. Moreover, digital rural development can not only generate high-quality local employment opportunities by fostering new business models [8] but also enhance human capital and community identity through innovative services such as remote education and online cultural services, thereby optimizing public service experiences via information equity. Collectively, these changes constitute a comprehensive ecosystem that enhances the “attractiveness” of rural areas, making it possible to address the weakening of RLFS.

As a key measure for achieving agricultural and rural modernization, the core of digital rural development policies lies in integrating new digital tools—such as digital infrastructure, digital governance, and digital public services—into the traditional rural economic system, thereby shaping a new external environment for rural labor employment and ultimately influencing individual employment decisions, particularly RLFS. Overall, digital rural development policies promote the further penetration of digital information technologies into rural areas. The establishment of digital information service platforms and remote online training platforms not only injects digital knowledge into the rural workforce but also provides residents with new digital services and tools. While enhancing the match between labor skills and job requirements, these initiatives also foster new rural business formats and transform traditional industries, thereby strengthening the long-term employment willingness of the labor force. Specifically, the direct effects of digital rural development policies on RLFS manifest in the following aspects:

First, the continuous improvement of digital infrastructure under policy promotion reduces both the spatial friction costs of cross-regional employment and the temporal friction costs of local employment for rural labor [9,10], enhancing the matching between labor demand and supply and thereby increasing individual RLFS. On the one hand, regarding spatial friction costs, geographic disparities in traditional labor markets often impose “market segmentation barriers” on rural labor. When local employment opportunities are scarce and cross-regional employment involves high risks, rural workers are compelled to engage in fragmented, temporary employment, which limits both their subjective RLFS and objective employment continuity. Digital rural development policies, through initiatives such as constructing digital base stations and promoting 5G deployment in rural areas, enhance digital infrastructure, reduce spatial friction costs in labor search, and mitigate market segmentation barriers caused by geographic differences. This alleviates labor misallocation due to information asymmetry, further strengthening the long-term employment willingness of labor individuals. For example, in Guiying Village, Longshan County, Hunan Province, the construction of a digital platform facilitated the active publication of convenience services and labor demand information, creating an online communication channel for the rural labor market. The platform also includes an “incident reporting” section, providing an accessible online feedback mechanism that enhances risk-avoidance capacity during cross-regional mobility, thereby supporting the improvement of RLFS. On the other hand, with respect to temporal friction costs, traditional agricultural labor relies heavily on past experience for planting decisions, resulting in path dependency, and the seasonal nature of farming leads to extended land idleness and seasonal unemployment [11]. Digital rural development policies enhance the application of agricultural sensors and big data platforms in crop cultivation, shortening average growth cycles, increasing annual planting batches per plot, and continuously improving agricultural production efficiency and stability. Consequently, labor willingness to engage in agriculture increases. Additionally, the development of remote online training enables laborers to improve their skills without reducing their planting efficiency, increasing their human capital stock and converting it into knowledge for subsequent planting decisions, thereby enhancing long-term agricultural RLFS.

Second, from the perspective of income utility, RLFS fundamentally reflects laborers’ employment decisions and work duration on the basis of the realized utility of different job-related incomes. When the actual utility derived from a given employment option exceeds that of alternatives, RLFS is reinforced. Traditional forms of rural employment, such as crop and livestock farming or casual labor, are characterized by low income levels, high vulnerability to natural risks and market price fluctuations, and limited opportunities for skill enhancement, resulting in low expected income utility and weak long-term employment intentions [12,13]. Digital rural development policies can enhance RLFS by both increasing the marginal returns of traditional employment activities and providing new avenues for career development. On the one hand, these policies promote the adoption of smart agriculture, precision agriculture, and agricultural big data management systems, digitally transforming the entire agricultural value chain and mitigating production-related natural risks and market risks in sales, thereby increasing income stability and average marginal returns. This strengthens laborers’ long-term employment intentions and RLFS within the agricultural sector. On the other hand, the integration of digital technology with traditional agriculture generates “agricultural new business models”, offering rural laborers new career development opportunities. Traditional agricultural work often suffers from low added value, labor intensity, and constrained career prospects, limiting skill and income growth and prompting labor outflow [14]. In contrast, digital integration fosters new agriculture-related positions such as live-streaming agriculture, e-commerce operations, and digital governance specialists, providing rural workers with alternative employment options. Participation in these new agricultural sectors enables laborers to obtain higher skill premiums and compensation, clarifying career trajectories and continuously enhancing RLFS. On the basis of the analysis above, we propose the following hypothesis:

H1.

The implementation of a digital rural development policy can significantly promote RLFS.

From the perspective of transmission mechanisms, the implementation of a digital rural development policy may influence RLFS through five pathways. First, the policy can enhance RLFS by increasing the degree of rural laborers’ integration into local social networks. Within a given region, digital rural initiatives leverage advances in digital technology and communication infrastructure to transfer social networks traditionally based on kinship and geographic proximity onto digital platforms, overcoming the small-group limitations inherent in conventional rural social ties [15,16]. As digital governance tools continue to improve, new social networks emerge, reshaping local network integration patterns and stabilizing employment activities. Across regions, community platforms such as WeChat and TikTok facilitate the maintenance and expansion of external social networks for rural residents, reduce barriers to cross-regional labor mobility, enhance belonging and identification for migrant workers, and strengthen their long-term employment intentions. Second, the policy can enhance RLFS by improving rural laborers’ digital literacy. Targeted training programs in smart agriculture management and data analytics for large-scale farmers and family farms increase their understanding of new agricultural models, bolster confidence in continued agricultural engagement, and lay the groundwork for further digital transformation. For migrant workers, remote skills training and management or operations courses provided under digital rural initiatives improve labor market skill matching, supporting access to stable employment positions.

Third, the implementation of a digital rural development policy can enhance RLFS by improving laborers’ health conditions. Imbalances in the supply and demand of medical resources have long constrained traditional rural labor, significantly affecting both work capacity and employment stability. With the ongoing development of digital rural infrastructure, integrated online-offline healthcare systems have gradually emerged. The rise in teleconsultations and online medical services reduces the costs and delays associated with seeking medical care for rural laborers [17]. The establishment of electronic health records increases transparency regarding workers’ health status, effectively preventing major illnesses while avoiding redundant medical expenses. These improvements mitigate sudden employment interruptions and strengthen RLFS.

Furthermore, the implementation of a digital rural development policy can enhance RLFS by reducing laborers’ speculative motives. For rural laborers engaged in agricultural production, the integration of the IoT and big data under the policy enables precision farming and better alignment of production with market demand, mitigating supply–demand fluctuations and price risks and thereby stabilizing operational returns. This ensures more predictable labor income expectations for agricultural workers [18,19]. The development of digital inclusive finance also provides smallholders with more accessible financing channels, alleviating liquidity constraints in agricultural operations, fostering long-term business confidence, and reducing speculative employment choices. For rural laborers engaged in off-farm work, the establishment of online data platforms increases transparency regarding job requirements, wage standards, and firm credibility, reducing information asymmetries that drive short-term, speculative employment behaviors, and thereby strengthening the RLFS between laborers and their current positions.

Finally, on the labor demand side, the implementation of a digital rural development policy can enhance RLFS by expanding the scale of labor demand. By continuously improving rural digital infrastructure, fostering digital industrial clusters, and promoting the digital transformation of traditional agricultural enterprises, the policy substantially broadens the development space for rural firms. As rural industry chains are strengthened and new industries and business models emerge, the labor demand structure shifts from predominantly manual work to a diversified mix of manual and technical tasks, increasing overall labor demand. This expansion not only generates sufficient local employment opportunities for rural laborers but also provides a stable job supply. Moreover, the availability of diverse positions allows rural laborers to match roles to their capabilities, reducing labor interruptions caused by poor job fit and thereby enhancing RLFS. Consequently, we propose the following hypothesis:

H2.

The implementation of a digital rural development policy influences RLFS through five channels: enhancing social network integration, improving laborers’ digital literacy, increasing health status, reducing speculative labor motives, and expanding the scale of enterprise labor demand.

2. Literature Review

The existing literature indicates that digital technologies and the digital economy have multidimensional and complex effects on labor markets. With respect to employment opportunities, some studies have reported that participation in the digital economy can significantly increase protective farming behaviors among rural households, thereby contributing to labor retention in the agricultural sector [20]. The impacts of digital skills vary. Some scholars have argued that digital skills, combined with the development of telecommunications infrastructure, primarily promote nonagricultural employment and entrepreneurial activities, with limited effects on agricultural employment [21,22]. Conversely, other studies have suggested that digital skills can simultaneously increase employment opportunities in both agricultural and nonagricultural sectors while reducing informal employment and enhancing overall employment security [23]. In terms of employment quality, rural digital infrastructure development also significantly improves the quality of nonagricultural employment [24].

In terms of labor mobility and stability, digital technologies have a dual effect. On the one hand, access to digital technologies significantly facilitates rural labor mobility [25]; however, the technologies themselves may introduce governance challenges. For instance, a comparative study in the German agricultural sector indicated that digital technologies can be used to intensify labor supervision and control, which may undermine worker autonomy and reduce work motivation [26]. Moreover, improvements in farmers’ digital literacy also drive employment transitions, manifested in increased local part-time work and extended periods of migrant labor [27]. On the other hand, digital technologies strengthen intravillage social networks and a sense of belonging, helping to mitigate labor outflow and promote collective action [28]. The development of inclusive digital finance further reinforces the promotion of nonagricultural employment [29,30].

In terms of the employment structure, the development of agricultural digital technologies has driven a profound transformation. This effect manifests as a coexistence of “substitution” and “creation”, with smart agriculture replacing certain low-skilled laborers while new business models such as e-commerce live streaming and online training generate additional employment opportunities [31]. Overall, the advancement of rural digital technologies facilitates the shift in rural labor from production-oriented positions to service-oriented and technical roles [32]. However, this process is accompanied by employment polarization and risk, as low-skilled workers may face marginalization [33], and the uncertainties associated with the development of rural e-commerce platforms introduce new risks for laborers [34].

Another key concept relevant to this study is labor flexibility, defined as the ability to reallocate labor across different sectors [35]. In contrast, labor stickiness, as a core measure of employment stability, embodies a multilayered connotation in the literat