학술논문
Profit Turnover Strategies and Future Directions for Coupang: Focusing on Logistics and Delivery
이용수 86
- 영문명
- Profit Turnover Strategies and Future Directions for Coupang: Focusing on Logistics and Delivery
- 발행기관
- 한국유통과학회
- 저자명
- Ye Jin CHO Jong Min BAEK Jung Ho KIM Jong Woo CHOI
- 간행물 정보
- 『유통과학연구(JDS)』제21권 제11호, 113~125쪽, 전체 13쪽
- 주제분류
- 경제경영 > 경제학
- 파일형태
- 발행일자
- 2023.11.30
무료
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국문 초록
영문 초록
Purpose: Coupang's profitability ratio has historically been low. However, both Coupang's sales and profitability started to improve in 2022. This paper aims to discuss Coupang’s strategy for turning itself into a profitable business.
Research design, data and methodology: Coupang is the company with the largest sales among the various domestic early-morning delivery companies and the only company with a surplus. It's shift into profitability will definitely have a big ripple effect on the early-morning delivery industry as a whole. Therefore, this report aims to investigate and divide Coupang's main business models and characteristics into two categories: logistics and delivery, identify the driving force behind the firm's turnaround, and predict its future based on theoretical models.
Results: Coupang maximizes economies of scale and enables continuous growth by making large-scale investments in logistics. It is ensuring more efficient delivery and reducing transportation costs by utilizing vendor flex, and it is expanding its product line while earning additional income through the CFS(Coupang Fulfillment Services) system.
Conclusions: Coupang's future outlook appears to be good, as it is the company that can most reliably procure fresh products in the long run thanks to its huge logistics center infrastructure.
목차
1. Introduction
2. Literature Review
3. Coupang’s Strategies
4. Discussion
5. Conclusion
References
해당간행물 수록 논문
- The Mediating and Moderating Role of Work-life Balance on Performance of Distribution Center Employees
- Profit Turnover Strategies and Future Directions for Coupang: Focusing on Logistics and Delivery
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- The Distribution of Failure in Medical and Health Insurance Claim: The Implications of Multiple Binary Logistic Regressions
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