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Case Study on Supply Chain Financing of Gree Electric Appliances

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DOI: 10.23977/infse.2024.050122 | Downloads: 9 | Views: 157

Author(s)

Ao Huan 1

Affiliation(s)

1 Heilongjiang University, Harbin, Heilongjiang, 150080, China

Corresponding Author

Ao Huan

ABSTRACT

In this paper, we delve into the intricate financial strategies of Gree Electric Appliances, a leading player in the global air conditioning market. Gree's journey, characterized by innovative approaches and strategic foresight, offers profound insights into modern financial management within a complex supply chain network. At the heart of Gree's success lies its use of financial instruments and sales models. Gree uses it not only as a tool to maximize profits, but also as an integral part of strengthening supply chain resilience and promoting symbiotic relationships with partners [1]. By examining Gree's adoption of the "payment before delivery" model and its nuanced application in bill endorsing and discounting, we uncover a strategic layering of financial practices that goes beyond conventional cash flow management. Additionally, the implementation of the "sales rebate" model and the "joint-stock region" sales strategy further illustrates Gree's commitment to cultivating a mutually beneficial ecosystem, aligning the interests of manufacturers and distributors toward shared goals. This exploration into Gree Electric Appliances' financial tactics illuminates how a blend of innovative sales techniques, astute financial planning, and collaborative relationships can coalesce to form a robust framework, capable of navigating market dynamics and enhancing competitive advantage. The insights gleaned from Gree's approach are not only pertinent to industry leaders and financial strategists but also offer valuable lessons for businesses endeavoring to thrive in today's intricate global market landscape.

KEYWORDS

Supply Chain, Gree Electric Appliances, Financial Analysis

CITE THIS PAPER

Ao Huan, Case Study on Supply Chain Financing of Gree Electric Appliances. Information Systems and Economics (2024) Vol. 5: 164-169. DOI: http://dx.doi.org/10.23977/infse.2024.050122.

REFERENCES

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