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.
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 practical 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 selection.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 prediction model will affect the next optimization decision objectives.This paper first proposes the focused information criterion(FIC)model selection criterion in the optimization of commodity income management,uses the FIC model selection criterion to select the product demand forecasting model,considers the structure of the optimization 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.
作者
王璐瑶
张新雨
邝雄
周建红
WANG Luyao;ZHANG Xinyu;KUANG Xiong;ZHOU Jianhong(School of Management,University of Science and Technology of China,Hefei 230026;Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing 100190;International Business School,Hainan University,Haikou 570228;Department of Credit Management,Guangdong University of Finance,Guangzhou 510521)
出处
《系统科学与数学》
CSCD
北大核心
2024年第3期809-823,共15页
Journal of Systems Science and Mathematical Sciences
基金
国家自然科学基金(71925007,72091212和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)资助课题。
关键词
决策
定价
需求预测
FIC模型选择
Decision
pricing
demand forecasting
FIC model selection
作者简介
通信作者:周建红,Email:jianhzhou86@163.com.
