Latent variable modelling of discrete choice experiments

离散选择实验的潜变量建模

• 批准号: DP0880074
• 负责人: Prof Jordan Louviere
• 金额: $ 17.51万
• 依托单位: University of Technology Sydney
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2008
• 资助国家: 澳大利亚
• 起止时间: 2008-02-01 至 2011-06-30
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP0880074
• 关键词: Latent; variable; modelling; discrete; choice

Discrete choice experiments and models are used to forecast consumer responses to changes in products policies and programs worldwide. Recent research suggests key model assumptions are violated because error variances covary with observed and unobserved factors. In order to address this, we will model systematic relationships between error variances and observed (eg, prices, survey length) and unobserved (eg, 'convenience', 'reputation') factors to improve model reliability and accuracy. This should lead to more accurate models/forecasts, benefitting business and government, which addresses the national priority of 'frontier technologies, promoting an innovative culture and economy'.

离散选择实验和模型被用来预测消费者对世界各地产品、政策和计划变化的反应。最近的研究表明，关键的模型假设被违反了，因为误差方差与可观察到的和未观察到的因素是一致的。为了解决这一问题，我们将建立误差方差与观测因素(如价格、调查长度)和未观测因素(如“便利性”、“声誉”)之间的系统关系模型，以提高模型的可靠性和准确性。这应该会产生更准确的模型/预测，使企业和政府受益，从而解决国家优先考虑的问题，即“前沿技术，促进创新文化和经济”。