Level overlap and level color coding revisited: Improved attribute attendance and higher choice consistency in discrete choice experiments

IF 2.8 3区 经济学 Q1 ECONOMICS Journal of Choice Modelling Pub Date : 2024-06-14 DOI:10.1016/j.jocm.2024.100494
Marcel F. Jonker
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Abstract

Previous work has identified attribute level overlap and level color coding as effective and attractive strategies to reduce task complexity and improve behavioral efficiency in discrete choice experiments (DCEs). However, the simultaneous and combined impact of level overlap and level color coding on attribute non-attendance and choice consistency has not yet been investigated. To address this limitation and to strengthen the available evidence base, this paper re-analyzed an existing randomized controlled DCE from the Netherlands (N = 2,731) and analyzed a new randomized controlled DCE conducted in the United Kingdom (N = 3,084) using heteroskedastic attribute non-attendance mixed logit models. Both randomized controlled experiments were based on a relatively complex instrument with 5 attributes with 5 levels each and the results from both experiments were remarkably similar. In the base-case study arms without level overlap and color coding, only about half of the attributes are attended to. Level color coding as a stand-alone strategy improves attribute attendance but reduces respondents' choice consistency. In contrast, level overlap as a stand-alone strategy improves attribute attendance while simultaneously increasing respondents' choice consistency. The combination of level overlap and color coding is even more effective: it results in approximately full attribute attendance and a 30% increase in respondents' choice consistency. Experimental designs with level overlap are therefore recommended as a default design strategy and level color coding recommended to further increase respondents’ behavioral efficiency in complex DCEs.

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水平重叠和水平颜色编码再探讨:在离散选择实验中提高属性出席率和选择一致性
以往的研究发现,在离散选择实验(DCE)中,属性水平重叠和水平颜色编码是降低任务复杂性和提高行为效率的有效且有吸引力的策略。然而,水平重叠和水平颜色编码对属性不关注和选择一致性的同时和综合影响尚未得到研究。为了解决这一局限性并加强现有的证据基础,本文重新分析了荷兰现有的随机对照 DCE(N = 2731),并使用异方差属性不出席混合 logit 模型分析了英国新进行的随机对照 DCE(N = 3084)。这两项随机对照实验都基于一个相对复杂的工具,其中包含 5 个属性,每个属性有 5 个等级,而这两项实验的结果非常相似。在没有级别重叠和颜色编码的基础研究臂中,只有大约一半的属性被关注。级别颜色编码作为一种独立策略提高了属性的出席率,但降低了受访者选择的一致性。与此相反,水平重叠作为一种独立策略,在提高属性出席率的同时,也提高了受访者选择的一致性。水平重叠和颜色编码的组合效果更好:它能使属性出席率达到近乎满分,并使受访者的选择一致性提高 30%。因此,建议将水平重叠实验设计作为默认的设计策略,并建议使用水平颜色编码来进一步提高受访者在复杂的 DCE 中的行为效率。
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来源期刊
CiteScore
4.10
自引率
12.50%
发文量
31
期刊最新文献
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