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基于主成分logistic回归模型的餐饮商务信息意识研究
引用本文:李红霞.基于主成分logistic回归模型的餐饮商务信息意识研究[J].重庆工商大学学报(社会科学版),2016,33(4):56-61.
作者姓名:李红霞
作者单位:重庆工商大学 管理学院,重庆 400067; 重庆工商大学 电子商务及供应链重庆市重点实验室,重庆 400067
基金项目:重庆市教委科学技术项目(KJ1400631);重庆市教育规划项目(2014-GX-092);重庆市企业管理研究中心开放基金项目;重庆市教委人文社会科学项目(14SKH07)。
摘    要:数据挖掘技术日趋成熟,广泛应用于金融、地产、投资、评估等各个领域。数据挖掘技术亦可应用于餐饮业,为其经营决策做出分析。其他领域的数据挖掘的成功案例也可以引用到餐饮行业中。本文对餐饮人士在餐饮商务中是否具备信息意识、对信息意识的重视程度进行调查,利用数据挖掘中主成分分析和 logistic 回归处理和分析收集来的数据,从而说明数据挖掘在餐饮业管理中的重要意义,反映餐饮人士信息意识状况。利用数据挖掘技术对餐饮商务资讯进行管理势必提高企业效率和盈利水平,促进餐饮业健康稳定的发展。

关 键 词:数据挖掘  餐饮商务  主成分分析  logistic  回归  信息意识

Research on the Catering Business Information Consciousness Based on Logistic Regression Model of Principal Component Analysis
Abstract:Data mining technology has become increasingly mature and has been widely used in financial,real estate,investment,e-valuation,banks and other fields.Data mining techniques can be applied to the catering industry to make analysis of its business deci-sions.Data mining in the field of other successful cases can also refer to the catering industry.This article has carried out the survey on whether the dining people in the restaurant business had information awareness and the extent the people emphasized information aware-ness.Principal component analysis and logistic regression in data mining process are used to analyze the collected data so as to illustrate the important value of data mining in the catering industry management and to reflect the restaurant information awareness of the dining people.Using data mining technology on food and beverage business information management is bound to improve business efficiency and profit level and to promote the healthy and stable development of the catering industry.
Keywords:data mining  catering business  principal component analysis  logistic regression  information awareness
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