实力加冕！全国仅 28 家 GONYOYO 荣耀入选“2026供应链服务创新与应用案例集”

The official results of the national supply chain service innovation and best practice case collection, along with the selected outstanding cases, offer valuable insights for general readers following real-economy operations and industrial development.

1. The selection carries strong industry credibility: hosted by the China Warehousing and Storage Association, the multi-month nationwide solicitation process went through preliminary document review, expert re-evaluation, and on-site research at shortlisted enterprises, with only 28 companies ultimately selected. All selected cases have had their practical outcomes independently verified by industry authorities.

2. The selected practice from the GONYOYO platform holds strong practical reference value. Its core model integrates three business segments—spot retail, cloud warehousing, and cloud manufacturing—leveraging digital intelligence to connect upstream and downstream players with diverse service resources, and designing actionable solutions focused on improving real-economy operational efficiency and easing financing constraints for small and medium-sized enterprises (SMEs).

3. Going forward, such platforms will continue refining their AI service capabilities, deepening industry-specific scenario coverage, and partnering with ecosystem players to build a collaborative supply chain network. Readers with operational needs may track open service access opportunities from these platforms.

The digital intelligent supply chain practices selected for the national supply chain innovation case collection provide an authority-validated reference for brands looking to optimize supply chain efficiency and improve channel layout.

1. The GONYOYO platform model delivers full-chain collaboration value: by integrating spot retail, cloud warehousing, and cloud manufacturing segments, it connects upstream and downstream enterprises with diverse service resources via digital intelligence tools. Brands partnering with such platforms can effectively close information gaps across retail, warehousing, and production links, reducing channel collaboration costs.

2. The platforms’ supporting services directly address core brand operational pain points. With solutions built specifically to improve real-sector service efficiency and ease SME financing strains, small and mid-sized brands can leverage these services to reduce capital pressure and speed up supply chain response times.

3. Digital industrial collaboration is a clearly established, industry-endorsed development direction. Early engagement with such innovative platforms will allow brands to build competitive advantages in upcoming channel efficiency competition.

The newly released outstanding national supply chain service innovation cases outline clear supply chain efficiency improvement pathways and high-quality, accessible resources for sellers, supporting cost reduction, performance gains, and lower operational risk.

1. The selected GONYOYO platform carries authoritative service endorsement: its AI-powered industrial internet application was selected among the 28 national outstanding cases following multiple rounds of rigorous review, ensuring service reliability. With an integrated layout covering spot retail, cloud warehousing, and cloud manufacturing, the platform provides sellers with end-to-end support spanning product selection, cloud warehousing fulfillment, and production-side connection.

2. Sellers can draw on its operational approach, prioritizing two core focus areas: improving fulfillment efficiency and optimizing capital turnover, while proactively partnering with high-quality third-party service providers to address internal capability gaps.

3. The platform will continue refining its AI capabilities and co-building a collaborative supply chain ecosystem going forward. Sellers can proactively engage with the platform to access ecosystem resource support and identify new operational growth opportunities.

The selected industrial internet innovation practices offer actionable reference pathways for factories pursuing digital transformation, order expansion, and resource connection, with clear commercial cooperation opportunities embedded.

1. The GONYOYO platform provides factories with a direct order connection channel. By integrating spot retail, cloud warehousing, and cloud manufacturing segments, it uses digital intelligence to link front-end retail demand, warehousing resources, and production-side capacity. Factories joining the platform can directly access real front-end retail demand, reduce unguided production, and secure stable order sources.

2. The “cloud factory” model offers a low-threshold path to digital transformation for factories: instead of building digital systems from scratch, factories can leverage the platform’s AI-powered digital intelligence capabilities to achieve precise matching between production and demand, lifting production efficiency.

3. Such platforms have built targeted services to ease SME financing constraints. Factories accessing the platform may be eligible for related financing support, alleviating capital pressure across production processes.

The results of the national supply chain service innovation case selection clearly illustrate current technology trends, core customer pain points, and proven effective solutions in the industrial service space, offering an authoritative reference for service providers’ business planning.

1. AI implementation in industrial internet scenarios is the core direction of supply chain innovation. GONYOYO’s selection as a national outstanding case for its AI industrial internet application confirms that digital intelligence and AI enablement have become the mainstream track for supply chain service upgrades.

2. The platform’s on-the-ground practice identifies two core pain points for current SMEs: low collaboration efficiency in real-economy operations, and widespread difficulty accessing financing during operations. These two pain points represent high-priority service opportunities for providers.

3. Service providers can reference the platform’s resource integration model, connecting fragmented resources across industry chains to build actionable, digital-powered service products focused on efficiency improvement and business hardship relief, aligned with customers’ real operational needs.

The selected GONYOYO practice, included in the national supply chain innovation case collection, provides an authority-validated reference model for industrial platforms’ operational direction, ecosystem building, and value positioning, with strong practical takeaways.

1. Industrial platforms must anchor their services in real, real-economy demand. The core reason for GONYOYO’s industry recognition is its consistent focus on building actionable solutions for two core goals: improving real-sector service efficiency, and easing SME financing constraints. Models disconnected from real-economy demand are unlikely to win industry and customer acceptance.

2. Platforms can reference its full-chain business construction path: integrating spot retail, cloud warehousing, and cloud manufacturing segments, connecting upstream and downstream enterprises with diverse service resources via AI and other digital intelligence tools, to build end-to-end service capabilities and increase appeal to all types of business entities.

3. Long-term platform development requires deep, ongoing focus on industry scenarios, continuous refinement of core technology capabilities, and collaboration with industry chain partners to build a sustainable supply chain ecosystem, avoiding the risk of decoupling business models from the real economy.

The 28 outstanding supply chain service innovation cases selected by the China Warehousing and Storage Association, particularly GONYOYO’s AI industrial internet practice, provide field-validated, empirical samples for industrial supply chain research, reflecting the latest industry development trends.

1. Supply chain innovation has now entered a substantive implementation phase: the integration of AI technology and industrial scenarios is no longer conceptual, and has formed a full-chain practice model connecting spot retail, cloud warehousing, and cloud manufacturing, eliminating information breakpoints across industry chain links via digital intelligence tools.

2. For common challenges faced by SMEs, including low operational efficiency and financing difficulties, market-oriented supply chain platforms have developed actionable solutions that support SME relief through resource integration and digital enablement. These practices hold significant research value.

3. Going forward, supply chain ecosystems will develop along the paths of continuous technology iteration, deep scenario penetration, and multi-stakeholder collaborative construction. This ecosystem development model offers real-world reference for industrial policy design and business model iteration research.