Although past research has tried to refine stated preferences elicited under discrete choice experiments (DCEs) by using methods to mitigate the hypothetical bias problem, little has been done to explore the consistency of preferences in repeated choice experiments. A key assumption of most DCEs is that individual’s preferences are stable across choice sets and remain unchanged throughout the experiment. However, it is possible that even little details in the experimental design, like changing the position of the alternatives within the same choice set, can hold a significant effect on choices. Using a within-subject experiment with eye tracking, we assess the influence of the position of the alternatives on the consistency of individuals’ choices. Specifically, we recruited 101 nonstudent participants from the general population in the Southern United States to participate in a 30-minute session. Participants received a $10 participation fee. Subjects ranged in age from 19 to 69, with an average of 28 years old and average income of $45,000. The experiment consisted of an ABA design that included three conditions and two “distraction tasks” between each treatment (Figure 1). The first condition was the baseline control, which entailed a standard DCE containing 12 hypothetical choice sets for vegetable products. In each choice set, subjects were asked to choose between three vegetable products and a “no-purchase” option. Each alternative was presented in four possible positions on the computer screen: 1) upper-left corner, 2) upper-right corner, 3) lower-left corner, and 4) lower-right corner. In the second condition, the “ position change treatment” , the same DCE was implemented; however, the position of the alternatives was randomized for each choice set. The third condition, referred to as the baseline treatment, replicated the original 12 choice sets in the baseline control (with the same positions for each alternative). In order to avoid subjects trying to memorize their choices in the baseline control and deliberately trying to match them in the baseline treatment, the order of the choice sets was randomized. Furthermore, two “distraction tasks” were included between the conditions in order to measure choice preferences after the subject’s attention was diverted (by manipulating the focus of attention). The first distraction task was a short socio-demographic survey presented between the baseline control and the position change treatment. The second distraction task was a cognitive function test commonly used to measure fluid intelligence. Figure 1 . Experimental Procedure. In this application, an orthogonal D-efficient fractional factorial design with no priors was generated using NGENE 1.1.2. Five artichoke vegetable attributes with three levels each were used: 1) size ( small, medium, large ), 2) color ( green, purple, mixed ), 3) production method ( conventional, organic, pesticide-free ), 4) presentation form ( fresh, canned, glass ), and 5) price ($1/unit, $2/unit, $3/unit ). In order to ensure that the subject was familiar with the attributes, a review of the definitions of each product attribute and attribute levels was presented prior to the baseline control condition. Theoretically the order of the choice sets and the position of the alternatives should not alter the subject’s preferences; however, we report evidence that both the position in which the alternatives are presented and the choice sets’ order influence which attributes the participants pay more attention to and ultimately, their choices. Overall, subjects searched for their preferred alternative in a “Z” motion, going from left to right and top to bottom, and the time they spent evaluating the different choice sets quickly decays as they progress through the experiment. Moreover, it appears that the alternatives located in the upper positions, especially the upper right position, received the highest attention in terms of how often subjects see those alternatives and how long they spend looking at them. This result ties into the relationship between the position of the alternatives and the frequency of choices. That is, subjects tend to choose the products located at the upper positions more often, with a higher inclination towards the alternative in the upper right position. The eye tracking results are further explored by estimating willingness-to-pay (WTP) space parameters. The distributions of WTP estimates differed significantly for nearly all attributes after changing the order of the choice sets and the position of the alternatives. Recall that the alternatives and choice sets are identical. However, after changing the position of the alternatives in the choice set, subjects selected the same alternative only 69% of the time. Furthermore, after reverting back to the original positions (baseline treatment), subjects consistently selected the same alternative only 67% of the time. The latter consistency level is a bit concerning considering that subjects were facing identical choice sets to those in the baseline control, only in different order. The results presented here highlight the importance of the position of the alternatives in the experimental design. The knowledge that even slight changes in the experimental design could significantly affect individuals stated preferences warrants more attention to detail when designing DCEs to elicit individuals’ valuations. That being said, the position of the alternatives, and the order of the choice sets should be taken as part of the experimental design in order to obtain more stable preference parameter estimates.

中文翻译：

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在离散选择实验中测试偏好的一致性：眼动追踪研究

尽管过去的研究试图通过使用减轻假设偏差问题的方法来改进离散选择实验 (DCE) 下的陈述偏好，但很少有人探索重复选择实验中偏好的一致性。大多数 DCE 的一个关键假设是个人的偏好在选择集上是稳定的，并且在整个实验过程中保持不变。然而，即使是实验设计中的小细节，例如在同一选择集中改变备选方案的位置，也有可能对选择产生重大影响。使用带有眼动追踪的受试者内实验，我们评估了备选方案的位置对个人选择一致性的影响。具体来说，我们从美国南部的一般人群中招募了 101 名非学生参与者参加了 30 分钟的会议。参与者获得了 10 美元的参与费。受试者年龄从 19 岁到 69 岁不等，平均年龄 28 岁，平均收入 45,000 美元。该实验由 ABA 设计组成，其中包括三个条件和每个处理之间的两个“分心任务”（图 1）。第一个条件是基线控制，它需要一个标准 DC​​E，其中包含 12 个假设的蔬菜产品选择集。在每个选择集中，受试者被要求在三种蔬菜产品和“不购买”选项之间进行选择。每个选项都在计算机屏幕上的四个可能位置呈现：1) 左上角，2) 右上角，3) 左下角，和 4) 右下角。第二种情况，“换位处理”，执行相同的DCE；然而，对于每个选择集，备选方案的位置是随机的。第三个条件，称为基线处理，在基线控制中复制了原始的 12 个选择集（每个选项的位置相同）。为了避免受试者试图记住他们在基线控制中的选择并故意尝试在基线治疗中匹配它们，选择集的顺序是随机的。此外，在条件之间包括两个“分心任务”，以测量受试者注意力转移（通过操纵注意力焦点）后的选择偏好。第一个分散注意力的任务是在基线控制和位置变化治疗之间进行的简短社会人口调查。第二个分心任务是认知功能测试，通常用于测量流体智力。图1 。实验程序。在此应用程序中，使用 NGENE 1.1.2 生成了无先验的正交 D 高效部分因子设计。使用了三个级别的五种朝鲜蓟蔬菜属性：1) 大小（小、中、大），2）颜色（绿色、紫色、混合），3）生产方法（常规、有机、无农药），4）外观形式（新鲜的、罐装的、玻璃的），和 5) 价格（$1/unit、$2/unit、$3/unit）。为了确保主体熟悉属性，在基线控制条件之前，对每个产品属性和属性级别的定义进行了审查。理论上，选择集的顺序和选项的位置不应改变主体的偏好；然而，我们报告的证据表明，提出替代方案的位置和选择集的顺序都会影响参与者更关注并最终影响他们的选择。总体而言，受试者以“Z”形运动从左到右、从上到下搜索他们的首选选项，并且他们评估不同选择集的时间随着实验的进行而迅速减少。此外，似乎位于上方位置的替代品，尤其是右上方的位置，在受试者看到这些替代方案的频率以及他们花多长时间看这些替代方案方面受到了最高的关注。这一结果与备选方案的位置和选择频率之间的关系有关。也就是说，受试者更倾向于选择位于上方位置的产品，对右上方位置的替代品的倾向更高。通过估计支付意愿 (WTP) 空间参数进一步探索眼动追踪结果。在改变选择集的顺序和备选方案的位置后，几乎所有属性的 WTP 估计分布都有显着差异。回想一下，备选方案和选择集是相同的。然而，在改变选项在选择集中的位置后，受试者只有 69% 的时间选择了相同的替代方案。此外，在恢复到原始位置（基线处理）后，受试者始终选择相同的替代方案的概率仅为 67%。考虑到受试者面临与基线控制相同的选择集，只是顺序不同，后者的一致性水平有点令人担忧。这里呈现的结果强调了替代方案在实验设计中的位置的重要性。在设计 DCE 以引发个人估值时，即使实验设计中的微小变化也会显着影响个人陈述的偏好，这一知识值得更多关注细节。话虽如此，替代品的位置，