Models for Heterogeneous Variable Selection
Models for Heterogeneous Variable Selection
复制标题
异质变量选择模型
DOI：
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发表时间：
2006
期刊：
影响因子：
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通讯作者：
Jeff D. Brazell
中科院分区：
文献类型：
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作者：
Timothy J. Gilbride;Greg M. Allenby;Jeff D. Brazell
偏好异质性是市场营销中的一个主要研究方向，旨在量化和理解产品属性和属性水平的需求多样性。在实验环境中，消费者提供简单的产品描述，连续分布的异质性，如多元正态分布，提供了一个有用的表示偏好。然而，在更复杂的情况下，受访者仅对与产品或认知限制相关的一些好处有价值，从而导致选择性关注可用信息的子集，异质性的连续分布并不反映子集的可能性变量对于不同受访者具有非零效应量。识别哪些属性用于品牌选择决策与变量选择的统计过程密切相关。本文扩展了变量选择方法，以适应消费者和数据环境的异质性，在市场营销研究中经常遇到的条件。作者将这些方法应用于一项离散选择联合研究，其中收集的数据以完整配置文件和部分配置文件格式。
Preference heterogeneity is a major research stream in marketing aimed at quantifying and understanding the diversity of demand for product attributes and attribute levels. In experimental settings, in which consumers are presented with simple descriptions of product offerings, continuous distributions of heterogeneity, such as the multivariate normal, provide a useful representation of preference. However, in more complex cases in which respondents have value for only a few of the benefits associated with an offering or cognitive constraints that result in selective attention to a subset of the information available, continuous distributions of heterogeneity do not reflect the possibility that a subset of the variables has nonzero effect sizes for different respondents. Identifying which attributes are used in a brand choice decision is closely related to the statistical procedure of variable selection. This article extends variable selection methods to accommodate heterogeneity across consumers and data contexts, conditions frequently encountered in marketing studies. The authors apply the methods to a discrete-choice conjoint study in which data are collected in both full-profile and partial-profile formats.
影响因子：
1.4
作者：
E. George;R. McCulloch
通讯作者：
E. George;R. McCulloch