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Heterogeneity distributions of willingness-to-pay in choice models

机译:选择模型中支付意愿的异质性分布

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We investigate direct and indirect specification of the distribution of consumer willingness-to-pay (WTP) for changes in product attributes in a choice setting. Typically, choice models identify WTP for an attribute as a ratio of the estimated attribute and price coefficients. Previous research in marketing and economics has discussed the problems with allowing for random coefficients on both attribute and price, especially when the distribution of the price coefficient has mass near zero. These problems can be avoided by combining a parameterization of the likelihood function that directly identifies WTP with a normal prior for WTP. We show that the typical likelihood parameterization in combination with what are regarded as standard heterogeneity distributions for attribute and price coefficients results in poorly behaved posterior WTP distributions, especially in small sample settings. The implied prior for WTP readily allows for substantial mass in the tails of the distribution and extreme individual-level estimates of WTP. We also demonstrate the sensitivity of profit maximizing prices to parameterization and priors for WTP.
机译:我们调查在选择设置中针对产品属性变化的消费者支付意愿(WTP)分布的直接和间接规范。通常,选择模型将属性的WTP标识为估计属性和价格系数的比率。市场营销和经济学领域的先前研究已经讨论了在属性和价格上都允许使用随机系数的问题,尤其是当价格系数的分布质量接近零时。通过将直接识别WTP的似然函数的参数化与WTP的正常先验值相结合,可以避免这些问题。我们表明,典型的似然参数化与被视为属性和价格系数的标准异质性分布相结合,导致后WTP分布表现不佳,尤其是在小样本环境中。 WTP的隐含先验很容易在分布的尾部产生大量质量,并且对WTP进行了极端的个人估计。我们还证明了利润最大化价格对WTP参数化和先验的敏感性。

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