考虑决策目标的FIC模型选择
FIC Model Selection Considering Decision Objectives
王璐瑶 1张新雨 2邝雄 3周建红4
作者信息
- 1. 中国科学技术大学管理学院,合肥 230026
- 2. 中国科学院数学与系统科学研究院,北京 100190
- 3. 海南大学国际商学院,海口 570228
- 4. 广东金融学院信用管理系,广州 510521
- 折叠
摘要
收益管理优化是提高零售商经济收益的有效途径之一.定价是收益管理的引擎和核心技术,对于提高零售商的收益具有重要作用.考虑到在收益管理的实际应用中,预测和优化问题的复杂性,通常采用先对产品需求进行预测,然后对收益进行优化的步骤.在对产品需求进行预测时,通常会面临多个候选模型,即面临模型的不确定性,这时一般会采用模型选择方法确定最终的模型.但传统的模型选择准则包括赤池信息准则(Akaike information criterion,AIC),贝叶斯信息准则(Bayesian information criterion,BIC)等通常只考虑了模型选择对预测精度的影响,而不考虑该预测模型会如何影响接下来的优化决策目标.本文首次在商品的收益管理优化中提出最小化聚焦信息准则(focused information criterion,FIC)这种模型选择准则,运用FIC模型选择准则选择产品需求预测模型,考虑了优化模型的结构,以最小化决策误差,而不是预测误差为目标,来选择预测模型.数值模拟结果表明,在大部分情况下,相比于AIC和BIC两种模型选择准则,考虑决策目标的FIC模型选择准则表现最佳.同时,实证研究结果也验证了考虑决策目标的FIC模型选择准则的优越性.
Abstract
The optimization of revenue management is one of the effective ways to improve retailers'economic returns.Pricing is the engine and core technology of revenue management,which plays an important role in improving retailers'revenue.Considering the complexity of forecasting and optimization problems in the prac-tical application of revenue management,the steps of forecasting product demand first and then optimizing revenue are usually adopted.When forecasting product demand,there are usually multiple candidate models,that is,facing the uncertainty of the model.At this time,the final model is generally determined by model se-lection.However,traditional model selection criteria,including Akaike information criterion(AIC)and Bayesian information criterion(BIC),usually only consider the impact of model selection on prediction accuracy,without considering how the pre-diction model will affect the next optimization decision objectives.This paper first proposes the focused information criterion(FIC)model selection criterion in the op-timization of commodity income management,uses the FIC model selection criterion to select the product demand forecasting model,considers the structure of the op-timization model,and selects the prediction model with the goal of minimizing the decision-making error rather than prediction error.The numerical simulation results show that,in most cases,compared with AIC and BIC model selection criteria,FIC model selection criteria considering decision objectives performs best.Meanwhile,the empirical research results also verify the superiority of the FIC model selection criteria considering decision objectives.
关键词
决策/定价/需求预测/FIC模型选择Key words
Decision/pricing/demand forecasting/FIC model selection引用本文复制引用
基金项目
国家自然科学基金(71925007)
国家自然科学基金(72091212)
国家自然科学基金(71963011)
教育部人文社会科学研究项目(22YJC630012)
广东省哲学社会科学规划项目(GD22XGL29)
出版年
2024
NETL
NSTL
万方数据