Risk‐Averse Optimization of Coordinated Dynamic Pricing and Working Capital Management in Omnichannel Retailing: A Conditional Value‐at‐Risk Approach

全渠道 盈利能力指数 现金流 计算机科学 利润(经济学) 灵活性(工程) 计量经济学 市场流动性 经济 库存控制 动态定价 存货投资 微观经济学 粒子群优化 运筹学 随机规划 现金 逆向选择 新颖性 灵敏度(控制系统) 强迫(数学) 动态规划 情景分析 业务 职位(财务) 适应性 代表(政治) 订单(交换) 提前期 客户关系管理 数学优化 最优化问题
作者
Milad BabaieFard,Mehdi Aghabeigi,Mohammad Reza Feylizadeh
出处
期刊:Journal of Applied Mathematics [Hindawi Publishing Corporation]
卷期号:2026 (1)
标识
DOI:10.1155/jama/7297922
摘要

The rise of omnichannel retailing lets customers engage retailers through multiple routes, including physical stores, online ordering, and hybrid fulfillment. Although this shift creates opportunities to grow sales and improve customer experience, it sharply increases the complexity of pricing, inventory, and financing decisions. When firms treat these domains in isolation, the result is often operational misalignment, higher costs, liquidity shortages, and lower profitability. This study develops an integrated model that jointly optimizes pricing, inventory, and financing decisions in an omnichannel retail system operating under uncertainty and risk. We formulate a multiperiod mathematical programming model spanning three principal sales channels that simultaneously determines selling prices, order quantities, inventory levels, sales volumes, and cash flows. A scenario‐based representation captures demand and environmental uncertainty, and the conditional value‐at‐risk (CVaR) criterion is embedded in the objective, so the model maximizes expected profit while explicitly controlling losses under adverse scenarios. Because it combines continuous and binary variables with nonlinear relationships, the model is solved using a particle swarm optimization (PSO) metaheuristic. Numerical results show a sound balance between profitability and risk control, with dynamic channel‐level pricing, economic batch ordering, efficient inventory allocation, and a sustained positive cash position as principal outcomes. Scenario analysis indicates stable performance under demand uncertainty and market volatility. Sensitivity analysis reveals that the risk‐aversion coefficient, initial capital, demand rate, interest rate, and cost strongly influence performance. These findings show that omnichannel success depends not only on higher sales but also on coordinating marketing, operations, and finance, aiding risk‐aware managerial decisions.
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