AN EMPIRICAL EVALUATION OF PARAMETER SENSITIVITY TO CHOICE SET DEFINITION IN SHOPPING DESTINATION CHOICE MODELS

AN EMPIRICAL EVALUATION OF PARAMETER SENSITIVITY TO CHOICE SET DEFINITION IN SHOPPING DESTINATION CHOICE MODELS
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购物目的地选择模型中参数对选择集定义敏感性的实证评估

DOI:
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发表时间:
2005
期刊:
影响因子:
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通讯作者:
Ge Lin
Ge Lin
中科院分区:
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文献类型:
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作者:
P. A. Pellegrini;A. Fotheringham;Ge Lin

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本文使用来自堀田州盖恩斯维尔的超市选择数据,实证检验了购物目的地选择背景下参数对选择集规范的敏感性。我们多次估计广泛应用的多项式 Logit (MNL) 离散选择模式的参数。对于所有观察,每个估计都使用通用选择集的单个随机选择的子集。针对特定细分市场和选择子集大小检查参数估计值的分布。结果表明,模型的参数对校准中使用的选择集的选择非常敏感。然而,这种敏感性并不适用于所有参数,并且存在一些有趣的变化。例如,距离威慑和连锁形象参数比商店规模和商店竞争参数表现出更高的稳定性。李补充说,模型参数显示出令人鼓舞的稳定性,具有相对较小的七到十家商店的选择集。
This paper empirically examines parameter sensitivity to choice set specification in the context of shopping destination choice, using supermarket choice data from Gainesville, Horida. We estimate parameters of the widely applied multinomial logit (MNL) discrete choice mode) multiple times. Each estimation uses, for all observations, a single randomly selected subset of the universal choice set. The distribution of parameter estimates is examined for specific market segments and choice subset sizes. The results indicate that the parameters of the model can be quite sensitive to the selection of the choice set used in the calibration. However, this sensitivity is not even across all parameters and there are some interesting variations. Distance deterrence and chain image parameters, for example, exhibit much more stability than parameters for store size and store competition. Li addition, model parameters show encouraging stability with relatively small choice sets of seven to ten stores.