CAJ | 학술논문

一阶自回归（AR（1））序列模拟需求过程是传统文献采用的经典模型，然而上述文献关于需求过程参数（如需求自回归系数）对牛鞭效应的影响分析缺乏实践意义，为了更符合企业的实际决策过程，本文建立了需求依赖于价格、而以AR（1）序列模拟价格过程的需求函数模型，分析了最小均方差、移动平均和指数平滑预测下的牛鞭效应，确定了零售商的预测技术选择条件。研究表明：（1）产品市场规模不影响零售商预测技术的选择；（2）当产品价格敏感系数较小或价格自回归系数较小时，零售商应选择最小均方差预测技术；（3）当产品价格敏感系数和价格自回归系数均较大时，零售商应选择移动平均预测技术。
일계자회귀（AR（1））서렬모의수구과정시전통문헌채용적경전모형，연이상술문헌관우수구과정삼수（여수구자회귀계수）대우편효응적영향분석결핍실천의의，위료경부합기업적실제결책과정，본문건립료수구의뢰우개격、이이AR（1）서렬모의개격과정적수구함수모형，분석료최소균방차、이동평균화지수평활예측하적우편효응，학정료령수상적예측기술선택조건。연구표명：（1）산품시장규모불영향령수상예측기술적선택；（2）당산품개격민감계수교소혹개격자회귀계수교소시，령수상응선택최소균방차예측기술；（3）당산품개격민감계수화개격자회귀계수균교대시，령수상응선택이동평균예측기술。
In the previous research, a first-order autoregressive(AR(1))process was adopted by most research-ers to describe the demand process .However, it is difficult to explain the managerial insights of the demand process characteristics, such as the demand correlation coefficient on the bullwhip effect .Our research considers a demand model where the demand depends on its price and the price follows an AR (1)process, we derive the analytical expressions of the bullwhip effect with minimum mean-squared error(MMSE), moving average(MA) and exponential smoothing(ES)techniques and deduce the conditions under which the retailer should choose the best forecasting technique.Results show that: first, the market demand scale does not influence the retailer ’s choice.Second, when the product price sensitivity coefficient is small , or when the price correlation coefficient is small, the retailer should choose MMSE technique .Third, for products with a large product price sensitivity coefficient and a large price correlation coefficient , the retailer should choose MA technique .