Health Economics Research Unit, University of Aberdeen, Aberdeen, UK.
Department of Economics, Ca' Foscari University of Venice, Venice, Italy.
Health Econ. 2021 Jun;30(6):1291-1305. doi: 10.1002/hec.4245. Epub 2021 Mar 19.
Multi-attribute choices are commonly analyzed in economics to value goods and services. Analysis assumes individuals consider all attributes, making trade-offs between them. Such decision-making is cognitively demanding, often triggering alternative decision rules. We develop a new model where individuals aggregate multi-attribute information into meta-attributes. Applying our model to a choice experiment (CE) dataset, accounting for attribute aggregation (AA) improves model fit. The probability of adopting AA is greater for: homogenous attribute information; participants who had shorter response time and failed the dominance test; and for later located choices. Accounting for AA has implications for welfare estimates. Our results underline the importance of accounting for information processing rules when modelling multi-attribute choices.
多属性选择在经济学中常用于评估商品和服务的价值。分析假设个体考虑所有属性，并在它们之间进行权衡取舍。这种决策是认知上的要求，通常会触发替代决策规则。我们开发了一种新模型，其中个体将多属性信息汇总到元属性中。将我们的模型应用于选择实验（CE）数据集，解释了属性聚合（AA）会提高模型拟合度。采用 AA 的概率更高的情况有：同质的属性信息；响应时间较短且未能通过优势测试的参与者；以及位于较后的选择。解释 AA 对福利评估有影响。我们的结果强调了在多属性选择建模时，考虑信息处理规则的重要性。
