Previous choice studies have proposed a way to condition the utility of each alternative in a choice set on experience with the alternatives accumulated over previous periods, defined either as a mode used or not in a most recent trip, or the mode chosen in their most recent trip and the number of similar one-way trips made during the last week. The paper found that the overall statistical performance of the mixed logit model improved significantly, suggesting that this conditioning idea has merit. Experience was treated as an exogenous influence linked to the scale of the random component, and to that extent it captures some amount of the heterogeneity in unobserved effects, purging them of potential endogeneity. The current paper continues to investigate the matter of endogeneity versus exogeneity. The proposed approach implements the control function method through the experience conditioning feature in a choice model. We develop two choice models, both using stated preference data. The paper extends the received contribution in that we allow for the endogenous variable to have an impact on the attributes through a two stage method, called the Multiple Indicator Solution, originally implemented in a different context and for a single (quality) attribute, in which stage two is the popular control function method. In the first stage, the entire utility expression associated with all observed attributes is conditioned on the prior experience with an alternative. Hence, we are capturing possible correlates associated with each and every attribute and not just one selected attribute. We find evidence of potential endogeneity. The purging exercise however, results in both statistical similarities and differences in time and cost choice elasticities and mean estimates of the value of travel time savings. We are able to identify a very practical method to correct for possible endogeneity under experience conditioning that will encourage researchers and practitioners to use such an approach in more advanced non-linear discrete choice models as a matter of routine.

中文翻译：

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经验作为对选择的调节效应：它是外生的还是内生的重要吗？

先前的选择研究提出了一种方法，可以在选择集中对每个备选方案的效用进行条件限制，该选择集中在先前时期积累的备选方案的经验上，定义为最近一次旅行中使用或未使用的模式，或最近一次旅行中选择的模式。旅行以及上周进行的类似单程旅行的次数。论文发现，混合 logit 模型的整体统计性能有显着提升，表明这种条件反射思想有其可取之处。经验被视为与随机分量的规模相关的外生影响，在这种程度上，它捕获了未观察到的影响中的一些异质性，清除了潜在的内生性。目前的论文继续研究内生性与外生性的问题。所提出的方法通过选择模型中的经验调节特征来实现控制函数方法。我们开发了两种选择模型，都使用陈述的偏好数据。该论文扩展了收到的贡献，因为我们允许内生变量通过称为多指标解决方案的两阶段方法对属性产生影响，该方法最初是在不同的上下文中针对单个（质量）属性实施的，其中第二阶段是流行的控制功能方法。在第一阶段，与所有观察到的属性相关的整个效用表达式取决于对替代方案的先前经验。因此，我们正在捕获与每个属性相关的可能相关性，而不仅仅是一个选定的属性。我们找到了潜在内生性的证据。然而，清除工作导致时间和成本选择弹性以及旅行时间节省价值的平均估计的统计相似性和差异。我们能够确定一种非常实用的方法来纠正经验条件下可能的内生性，这将鼓励研究人员和从业者在更高级的非线性离散选择模型中使用这种方法作为常规问题。