关键词: 智慧农业, 数据驱动, 智能决策, 新质生产力, 农业基础模型, 开放协同, 大国小农

Abstract:

[Significance] Smart agriculture represents a strategic choice for addressing the global challenges of food security, climate change, and an aging agricultural labor force, and for cultivating new-quality productive forces in agriculture. Shaped by factors such as factor endowments, institutional traditions, and value preferences, economies have not converged upon a single optimal path, but have instead formed highly heterogeneous practical configurations across driving actors, institutional environments, technological pathways, and value orientations. Existing research remains largely confined to the parallel enumeration of country-specific experiences and lack a unified comparative framework; their mechanistic explanations seldom move beyond the single dimension of factor endowments, leaving the multidimensional, co-evolutionary dynamics inadequately understood. In view of this, the archetypal models of global smart agriculture were systematically compared, the mechanisms underlying their divergence were uncovered, and their evolutionary trends were assessed, so as to provide theoretical references and practical guidance for China to build an autonomous, controllable, and openly collaborative smart agriculture system and in advancing from technological follower to co-builder of rules. [Progress] Drawing on the theory of induced innovation and a comparative institutional analysis perspective, a four-dimensional analytical framework of "driving actors-institutional environment-technological pathway-value orientation" was constructed, and five representative economies, the United States, the European Union, Japan, Israel, and China, were selected to distill five archetypal models. The commercialized large-scale farm model exemplified by the United States is one in which the private sector leads and releases economies of scale through large-scale field operations. The green and intensive model exemplified by the European Union is one in which intensive production is steered by binding green constraints. The refined collaborative model exemplified by Japan is one in which platform-based co-governance alleviates super-aging and smallholder fragmentation. The water-saving innovative model exemplified by Israel is one in which a full-chain water-saving technology system has developed under acute water scarcity. The integrated collaborative model exemplified by China is one in which national strategy integrates multiple actors, coupling the 'large-country-with-smallholders' condition with leading digital infrastructure such as BeiDou, 5G, and AI. On this basis, four mechanisms, induced innovation, path dependence, the antitrust tradition, and rule-based contestation, were introduced to provide a process-tracing account of model divergence in terms of sequential triggering and tension-laden coupling, the underlying drivers of this divergence were traced across the three dimensions of endowment constraints, organizational systems, and value hierarchies, and thereby the distinct value sequences of the five models were identified. Five dimensions of global evolutionary trends were assessed: technology, organization, data, value, and governance. Technologically, from digital precision operations toward intelligent autonomous decision-making. Organizationally, from single-actor-driven development toward open-ecosystem co-governance. In data terms, from isolated silos toward cross-border interoperability and factor marketization. In value terms, from a singular pursuit of yield growth toward green, low-carbon, and resilience-oriented goals, and in governance, from national fragmentation toward global regulatory coopetition. [Conclusions and Prospects] Model divergence constitutes a stable equilibrium under the multiple coupling of factor endowments, institutional structures, and historical paths, and no universally optimal model exists; beneath this divergence lies a convergent core in which data serve as a factor of production, models as the decision-making engine, ecosystems as the organizational form, and sustainability as the value baseline. Looking ahead, global smart agriculture should evolve along the trajectory of technological inclusiveness, ecological openness, value pluralism, and governance synergy. China is well positioned to assume the composite role of technology provider, institutional experimenter, and rule co-builder, working with other nations to advance global smart agriculture toward a more inclusive and symbiotic configuration.

Key words: smart agriculture, data-driven, intelligent decision-making, new quality productive forces, agricultural foundation models, open collaboration, large country with smallholder farming