【摘要】 县城作为我国城镇体系的重要组成部分，是深入推进乡村全面振兴和以人为核心的新型城镇化的重要载体。本文通过甘肃省陇南市的案例研究和全国层面的实证分析，探讨了数字技术的任务偏向性对县域城镇化的影响及其内在机制。案例研究表明，政府主导的数字技术应用催生了电子商务、“数字+”等产业场景，推动县域劳动力市场向非常规任务密集型转变。在政策与平台协同赋能下，具备非常规任务属性的农村劳动力得以实现就业转变，从而推动以“就近就地”为特征的县域城镇化。实证研究发现，农村劳动力的非常规任务属性越高，其在电子商务冲击下实现县域内非农就业的概率越大。机制检验表明：电子商务冲击一方面显著促进了县域电商企业数量增加与新就业岗位创造；另一方面使得具备非常规任务属性的农村劳动力更多向第二、三产业转移，成为经营者和受雇者。本文融合案例研究的深入性和实证分析的一般性，揭示了任务偏向性在数字技术驱动县域城镇化中的关键作用，为分类推进以县城为重要载体的城镇化建设提供了学理依据和政策参考。更多还原

【Abstract】 County towns constitute a vital part of China’s urban system and serve as crucial vehicles for advancing comprehensive rural revitalization and people-centered new urbanization. However, the current county urbanization rate significantly lower than the national average. This gap stems primarily from insufficient industrial support and a consequent lack of employment opportunities. It impedes rural residents from entering county towns for non-agricultural employment and urban identities, and thus slows the pace of county urbanization.As new-generation digital technologies are deployed, the modes of production and work in county towns have been transformed, opening a new channel for absorbing rural labor and advancing county urbanization. Theoretically, digital technology can alter existing modes of production and create tasks or jobs with higher wages, thereby attracting rural labor into counties and ultimately driving county urbanization. Nevertheless, existing research indicates that digital technology is task-biased, tending to substitute for routine tasks while creating jobs involving more complex tasks. This characteristic suggests that digital technology may create employment thresholds through its task bias, which could affect the effectiveness of rural labor transfer into the county-level non-agricultural sector.This paper adopts a combination of case study and empirical analysis methods to explore how taskbiased digital technology influences rural labor employment choices and county urbanization. First, based on a representative case from Longnan City, this paper reveals the process through which digital technology drives county urbanization: local governments create more jobs involving non-routine tasks by introducing digital technologies; rural labor acquires relevant skills in pursuit of higher wages, achieving a transition from agricultural to non-agricultural employment, ultimately promoting county urbanization. Furthermore, the empirical analysis confirms our case findings. Results indicate that rural workers with higher densities of non-routine tasks are more likely to change employment types under the impact of e-commerce. Mechanism analysis shows that the e-commerce shock facilitates the entry of e-commerce-related enterprises and enhances their job creation capacity. Meanwhile, rural workers performing non-routine tasks are more likely to shift from the primary industry to the secondary and tertiary industries, and transition from farming to wage employment or self-employment.This paper makes contributions in the following two aspects. First, it examines how rural labor achieves occupational transformation under digital technology shocks from the perspective of task bias, thereby advancing county urbanization. While existing research has primarily examined how digital technology affects rural employment and income,the specific role of its task-biased nature in promoting county urbanization remains unexplored.By revealing the differential impacts of digital technology’s task bias on urbanization at the county level, this paper expands the theoretical mechanisms for promoting county urbanization and provides a new perspective for understanding how digital technology facilitates this process. Second, this paper combines case analysis with empirical research to provide qualitative and quantitative evidence on how task-biased digital technology can better drive county urbanization. In the case analysis, this paper deeply illustrates how e-commerce, through the diffusion of non-routine tasks, cultivates a labor market aligned with digital technology, thereby facilitating occupational transitions for rural labor and county urbanization. In the empirical research, this paper employs a large language model to identify the task attributes of occupations at a granular level, thus more precisely identifying the impact of digital technology shocks on workers of varying task attributes.更多还原