In the rapidly evolving landscape of agriculture and digital technology, a groundbreaking study sheds new light on how big data products are reshaping income distribution among e-commerce farmers in China. This research tackles an urgent and complex issue: the widening income disparities in rural communities amid technological advancements. While prior investigations primarily examined traditional digital divides focusing on mobile phones, computers, and internet access, this pioneering work dives deeply into the underexplored domain of big data, particularly relating to e-commerce platforms and their impact on farmers’ entrepreneurial success and economic equality.
Big data technologies are increasingly becoming pivotal in rural China, where many households engage in e-commerce, morphing from conventional farmers into digital entrepreneurs. The integration of advanced analytics tools developed by e-commerce platforms equips these farmers with scientifically grounded data-driven insights to optimize their online store operations. This marks a significant departure from older farming models dependent on incremental experience. Such big data applications enable low-income e-commerce farmers to enhance their entrepreneurial alertness and dynamic capabilities—traits crucial for navigating competitive digital marketplaces. The study’s findings demonstrate that these tools contribute to closing the income gap, suggesting a promising mechanism for promoting shared prosperity in rural economies.
The significance of this research extends beyond the Chinese context, offering a conceptual framework applicable to diverse developing countries aspiring to uplift their digital agricultural sectors. Unlike previous qualitative studies emphasizing public agricultural databases managed by governments, this research quantitatively analyzes micro-level data drawn from platform-developed commercial big data products. These data sets are characterized by massive volumes, rapid updates, and direct relevance to commodity market trends—attributes that fundamentally differentiate them from conventional government databases. Platform companies monetize and distribute these data products through market transactions, creating a new ecosystem of data accessibility that fuels entrepreneurial opportunities in rural settings.
One of the key theoretical contributions of this study lies in refining the technology acceptance model within the context of big data products. Traditionally, usefulness and ease of use have dominated this model’s explanatory power regarding technology adoption. However, the researchers argue and empirically confirm that these dimensions alone fail to capture the full spectrum of factors influencing e-commerce farmers’ engagement with big data tools. They introduce a third crucial dimension: the holistic experience of the product. This experience encompasses perceptions of risk, pricing fairness, emotional satisfaction, human-centered design, and even elements of green health. The findings emphasize that for the younger generation of e-commerce farmers—who actively embody the experience economy—the subjective quality of product interaction significantly drives adoption and continued use.
Practically, this study’s implications urge governments and industry players to rethink their strategies toward digital agriculture. Governments must acknowledge the untapped economic and social potential embedded in big data resources by establishing comprehensive, user-friendly agricultural databases that heighten usability and enrich user experience. Adopting diversified and standardized policies to regulate data resource utilization without stifling innovation represents a critical balance highlighted by the Chinese case. China’s unique approach—initially nurturing e-commerce growth and later introducing regulated oversight—offers a replicable model for other developing countries striving to harmonize technological adoption with regulatory environments.
From the enterprise perspective, platform companies hold a pivotal role in catalyzing broader adoption of big data products among rural farmers. Enhancing the intrinsic attributes of these tools—namely usefulness, simplicity, and especially user experience—will directly influence farmers’ attitudes and behaviors. Strategies such as offering more trial functionalities can alleviate initial hesitation, fostering trust and familiarity that eventually translate into sustained usage. This iterative process strengthens the capacity of e-commerce farmers to maximize returns and close entrepreneurial gaps fueled by data asymmetry.
For the farmers themselves, the message is equally vital. Embracing big data tools requires shifts in mindset and willingness to explore new technological frontiers beyond legacy farming practices. Increased entrepreneurial alertness—defined as the capability to identify and exploit emerging business opportunities—and bolstered dynamic capabilities enable farmers to continually innovate and adapt within volatile market spaces. Those who resist change risk obsolescence; conversely, proactive adopters can preserve competitiveness and secure upward mobility within the transformed rural economy.
At a granular level, the study elucidates how big data products help democratize access to vital market intelligence, enabling smaller or lower-income farmers to catch up with previously advantaged peers. The “experience” attribute particularly bridges psychological and practical divides, overcoming barriers associated with perceived complexity or uncertainty. Thus, big data adoption does not merely represent a technological upgrade but symbolizes a profound social leveling force with tangible income equality benefits.
This research also critically examines prior literature’s limitations that predominantly focused on government-led agricultural databases with public data attributes, usually discussed qualitatively. By contrast, this empirical investigation into platform-driven, commercially deployed big data products provides robust quantitative evidence on microeconomic impacts. The scale and velocity of these datasets, along with their market-responsive nature, make them especially potent in influencing farmers’ operational decisions and income trajectories.
Moreover, embedding the dimension of experience in product attributes grounded in the technology acceptance model answers a significant gap in existing research. The study’s empirical results reveal that while perceived usefulness and ease of use are indispensable, the user experience exerts a stronger marginal effect on farmer uptake of big data tools. This insight encourages developers and policymakers alike to innovate not just in utility and interface design but also in enriching the subjective dimension that governs real-world adoption.
China’s exceptional development trajectory in rural e-commerce plays a crucial contextual role in realizing this transformation. Heavy investments in digital infrastructure, robust platform ecosystems, and seamless logistics networks have created fertile ground for big data product innovation. Government openness to nurturing emerging sectors before regulating them ensures that innovators are not unduly constrained in the initial phases, thus fueling rapid industry growth and diffusion of technological benefits in the agricultural domain.
Importantly, while the study centers on China, its conceptual explanations and empirical findings present a framework transferable to other developing countries with similar ambitions. The general theoretical mechanism whereby big data products enhance entrepreneurial alertness and dynamic capabilities, thereby reducing income inequality, applies broadly. However, successful replication depends on local infrastructural readiness, regulatory sophistication, and cultural receptivity to digital innovations.
The march toward a data-driven rural economy heralds a new era where farming no longer hinges solely on accumulated knowledge over time but evolves dynamically in response to real-time digital insights. Big data empowers e-commerce farmers to leapfrog traditional barriers, fostering greater economic inclusivity and resilience. Meanwhile, the study’s comprehensive approach to understanding product attributes provides nuanced guidance for optimizing technology adoption strategies in marginalized communities.
In conclusion, this seminal research underscores big data products’ profound potential to mitigate income disparities among e-commerce farmers by bridging critical entrepreneurial capability gaps. By integrating cutting-edge analytics into rural livelihoods, it charts a viable pathway toward common prosperity in the digital economy era. Governments, platform companies, and farmers collectively stand to gain from embracing this transformation, which promises to redefine agricultural development paradigms and socially inclusive growth models worldwide.
Subject of Research:
The impact of big data products on income inequality among e-commerce farmers in China.
Article Title:
Big data products and income inequality of e-commerce farmers: evidence from China.
Article References:
Cui, Y., Li, L., Zeng, Y. et al. Big data products and income inequality of e-commerce farmers: evidence from China. Humanit Soc Sci Commun 12, 1400 (2025). https://doi.org/10.1057/s41599-025-05731-w
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