Life-cycle foods (such as soy products, dairy products, and bread) face dual supply and demand uncertainties in the supply chain due to long production lead times, short sales cycles, and large demand fluctuations. This study constructs a three-tier supply chain model with uncertain supply and demand for short-life-cycle foods, integrates data analysis and risk control methods, and quantifies the risk transmission path. The study finds that under decentralized decision-making, demand uncertainty leads to a reduction in retailer ordering quantity, which in turn triggers a decrease in supplier production, resulting in significantly lower supply chain profits compared to centralized decision-making levels. A single coordination contract (such as a manufacturer-led buy-back contract or a retailer-led option contract) can incentivize retailers to increase ordering quantity through the buy-back price or option mechanism, achieving Pareto improvement in the supply chain. When considering supply uncertainty, a combination contract is designed for both supplier and manufacturer alliances (where the retailer bears the alliance's raw material procurement costs and the alliance provides buy-back subsidies) and non-alliance (where the supplier and manufacturer jointly subsidize the retailer and share each other's costs), which can achieve shared supply and demand risks, enhance the profits of alliance members, and optimize overall revenue distribution. In management practice, retailers need to choose options or buy-back contracts based on their own bargaining power to reduce demand risks; when the manufacturer leads, excess products can be bought back to incentivize ordering, and when the retailer leads, mutually beneficial contracts need to be developed through cooperation; suppliers need to participate in risk sharing or form alliances with manufacturers to enhance efficiency and risk prevention capabilities.

Zelin Wang. Data Analysis and Risk in Supply Chain Management. International Journal of Social Sciences and Economic Management (2026), Vol. 7, Issue 1: 132-140. https://doi.doi.org/10.3807/IJSSEM.2026.070114.

[1] Zhao C , Yu W .Low-rank characteristic and temporal correlation analytics for incipient industrial fault detection with missing data[J].Spatio-Temporal Learning and Monitoring for Complex Dynamic Processes with Irregular Data, 2025:13-37.

[2] Wang L , Hua S , Liu Y ,et al.Evolutionary game dynamics of index insurance with refund or non-refund risk sharing mechanism[J].CHAOS, 2025, 35(5):053116.DOI:10.1063/5.0270353.

[3] Kitanovski V , Lutovska M , Trifunov Z ,et al.Incorporating nexus ecolabels into household level food waste mitigation strategies: Environmental perspectives from life cycle assessment[J].Journal on Processing and Energy in Agriculture, 2025, 29(1):18-28.DOI:10.5937/jpea29-56703.

[4] Zhen Zhong. Big Data Engineering and Intelligent Analysis Framework for Compliance Investigation. Academic Journal of Computing & Information Science (2025), Vol. 8, Issue 11: 107-115

[5] Ye, J. (2025). Design of a Non-Invasive Brain Computer Interface System for Handwritten Text Based on L2 Regularization and Attention Supervision Paradigm, and Optimization of EEG Signal Decoding. International Journal of Big Data Intelligent Technology, 2025, 6 (1), 126, 134.

[6] Ye, J. (2025). Challenges and Future Development of Neural Signal Decoding and Brain-Computer Interface Technology. Journal of Medicine and Life Sciences, 1(3), 54-60.

[7] Wu, W. (2025, June). Construction and optimization of intelligent gateway software management platform based on jenkins cluster management under cloud edge integration architecture in industrial internet of things. In International Conference on 6G Communications Networking and Signal Processing (pp. 633-645). Singapore: Springer Nature Singapore.

[8] Wu, L. (2025, December). Design and Application of Automatic Data Set Generation Tool Based on KLEE in Embedded Memory Management Performance Test Framework. In 2025 IEEE 17th International Conference on Computational Intelligence and Communication Networks (CICN) (pp. 1111-1117). IEEE.

[9] Truong, T. H. (2026). Research on Risks and Countermeasures of Enterprise E-Commerce Transformation in the Cross-Border E-Commerce Environment.

[10] Qi, Y. (2025, October). Research on Privacy Protection of AI Models in Big Data Using Differential Privacy Technology. In 2025 2nd International Conference on Software, Systems and Information Technology (SSITCON) (pp. 1-5). IEEE.

[11] Hong, Y. (2025). Architecture Design and Performance Optimization of a Large-scale Online Simulation Platform for Business Decision-making. Advances in Computer and Communication, 6(4).

[12] Hong, Y. (2026). Research on Warehouse Capacity Optimization Methods Based on Predictive Modeling. Engineering Advances, 6(1).

[13] Truong, T. H. (2025). Research on the Application of Digital Healthcare Platforms in Chronic Disease Management. Advances in Computer and Communication, 6(5).

[14] Ye, J. (2025). Optimization of Neural Motor Control Model Based on EMG Signals. International Journal of Engineering Advances, 2(4), 1-8.

[15] Zhang, X. (2025, May). Automobile Finance Credit Fraud Risk Early Warning System based on Louvain Algorithm and XGBoost Model. In 2025 3rd International Conference on Data Science and Information System (ICDSIS) (pp. 1-7). IEEE.