Modeling Multi-Year Customers’ Considerations and Choices in China’s Auto Market Using Two-Stage Bipartite Network Analysis
Modeling Multi-Year Customers’ Considerations and Choices in China’s Auto Market Using Two-Stage Bipartite Network Analysis
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使用两阶段双向网络分析对中国汽车市场的多年客户考虑因素和选择进行建模
DOI：
10.1007/s11067-021-09526-9
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发表时间：
2021
影响因子：
2.4
通讯作者：
Chen, Wei
中科院分区：
文献类型：
--
作者：
Bi, Youyi;Qiu, Yunjian;Sha, Zhenghui;Wang, Mingxian;Fu, Yan;Contractor, Noshir;Chen, Wei
选择建模在交通规划、市场营销和工程设计中具有重要意义，因为它可以量化产品属性和客户人口统计对客户选择行为的影响。消费者研究表明，消费者的选择过程通常包括两个不同的阶段：消费者首先考虑市场上可用产品的子集，然后从子集中做出最终选择。由于现有的偏好建模主要集中在选择阶段，因此有必要开发方法来理解两个阶段的客户偏好，并研究客户偏好如何从“考虑”转变为“选择”，以及这种变化是否会随着时间的推移而保持一致。本文使用多年的调查数据集，研究了中国汽车市场中消费者的考虑和购买行为。我们展示了描述性网络分析和分析网络模型（二部指数随机图模型（ERGM））如何捕捉客户偏好在连续多年从考虑阶段到选择阶段的变化。我们的研究结果表明，单位功率油耗、汽车制造原产地和生产地点等因素以不同的方式影响客户的考虑和最终购买决策，并且这种考虑和购买之间的差异是一致的。本研究的主要贡献在于，我们使用多年数据集验证了基于两阶段网络的建模方法及其在偏好激发中的效用，这有助于理解客户多年来的考虑和选择行为趋势。我们的研究还有助于通过将连续变量分类到范围来对ERGM结果进行精细解释，这表明客户选择决策可能更多地受到产品属性的定性影响，而不是定量影响。我们的方法是通用的，因此可以应用于解决更广泛的选择建模问题，例如运输方式的选择和清洁技术（例如，电动汽车）的采用。
Choice modeling is important in transportation planning, marketing and engineering design, as it can quantify the influence of product attributes and customer demographics on customers’ choice behaviors. Consumer studies suggest that customers’ choice-making process often consists of two different stages: customers first consider subsets of available products on the market, and then make the final choice from the subsets. As existing preference modeling is mostly focused on the choice stage, there is a need to develop methods for understanding customer preferences at both stages, and investigate how customer preferences change from “consideration” to “choice”, and whether such changes will be consistent over time. In this paper, we study customers’ consideration and purchase behaviors in China’s auto market using multi-year survey datasets. We demonstrate how descriptive network analysis and analytic network models (bipartite Exponential Random Graph Model (ERGM)) capture the change of customers’ preferences from the consideration stage to the choice stage in multiple consecutive years. Our results show that factors such as fuel consumption per unit power, car make origin, and place of production influence customers’ considerations and final purchase decisions in different ways, and this difference between consideration and purchase is consistent over time. The main contribution of this study is that we validate the two-stage network-based modeling approach and its utility in preference elicitation using multiple-year dataset, which sheds lights on understanding the trend of customers’ consideration and choice behaviors across years. Our study also contributes to a refined interpretation of the ERGM results with categorization of continuous variables into ranges, which shows that customer choice decisions may be more qualitatively influenced by product attributes rather than quantitatively. Our approach is generic and thus can be applied to solving broader choice modeling problems, such as the transportation mode selection and the adoption of clean technology (e.g., electric vehicles).
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