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Regression and Endogeneity Bias in Big Marketing Data
被引:1
|作者:
Kaur, PankajDeep
[1
]
Arora, Sumedha
[1
]
机构:
[1] Guru Nanakdev Univ, Rc Jalandhar 144001, India
来源:
关键词:
regression;
endogeneity;
decision;
variables;
D O I:
10.1016/j.procs.2015.10.025
中图分类号:
TP18 [人工智能理论];
学科分类号:
081104 ;
0812 ;
0835 ;
1405 ;
摘要:
Big marketing data offers more interesting and challenging problems but along with greater opportunities. These days calibration is performed in the marketing field for supporting the managers in marketing-mix decisions. It is also done to create general knowledge that paves a way for better understanding of marketing relationships. Hence it indirectly supports decisions. The marketing data is adulterated with endogeneity and the regressions, both requiring optimizable response model. The models should always be implementable if actual decision support is the objective. Endogeneity can be removed with the help of structural equations. Owing to this endogeneity challenge it is difficult to understand how the managers can reach their decisions. Endogeneity removal allows improvement in managerial decision-making (C) 2015 The Authors. Published by Elsevier B.V.
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页码:41 / 47
页数:7
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