IA Understanding the Effects of Choice Set Complexity in Stated Preference Methods

IA 了解指定偏好方法中选择集复杂性的影响

• 批准号: 9976541
• 负责人: George DeShazo
• 金额: $ 10.96万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-10-01 至 2002-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9976541&HistoricalAwards=false
• 关键词: IA; Understanding; Effects; Choice; Set

Economists employ stated preference methods to measure the use and non-use value that consumers derive from a variety of environmental programs. Recently, economists and federal agencies have begun to explore the feasibility of generalizing stated preference methods by moving from the contingent valuation method to so-called conjoint methods. The contingent valuation method presents consumers with only one alternative, for which the price varies, while conjoint methods present consumers with a choice set that contains several alternatives that each vary along a number of attributes. Proponents of conjoint analysis argue that this allows a more complete characterization of the benefits derived from the project's attributes, and may do so with greater statistical efficiency and lower financial costs than traditional stated preference methods. However, several prominent economists have expressed concern that the highly complex choice sets used in conjoint analysis may overwhelm the cognitive capacities of consumers and thus lead to unreliable estimates of use and non-use value. This debate continues because there is very little research about the effects of choice set complexity on estimates of economic benefits. As a result, public agencies such as EPA and NOAA are still uncertain as to the relative merits of conjoint methods versus other non-market valuation techniques. This uncertainty impedes the acquisition and use of information on economic benefits in judicial, regulatory and public investment decisions. We step into this debate with some rigorous and systematic research on the core issue: How does the complexity of a choice set affect the way in which a consumer reveals his value for environmental amenities? To answer this question, we vary the complexity of the choice set in an elaborate stated preference experiment and then evaluate choice outcomes with regard to several dimensions of the experiment. First, how does choice inconsistency (i.e., the propensity to make mistakes) vary with complexity? Second, do consumers' information processing strategies vary with the level of choice set complexity in a way that significantly changes their choices (and thus economists'estimates of benefits)? Third, how do the personal characteristics of consumers interact with choice set complexity to affect choice consistency and information processing strategies? Fourth, how are consumers' subjective assessments of choice set complexity related to the measures of complexity that we, as researchers, can objectively quantify? Answering these substantive questions will enable us to identify the limits of current practice and to extend the frontiers of research on stated preference methods. At the center of our analysis is a behavioral model of choice that integrates several strands of existing literature in the fields of psychology, economics and marketing. From this model, we develop a set of hypotheses that we can test statistically in order to provide answers to the above questions. By testing these hypotheses, we will develop methods to identify and control for choice set complexity in stated preference applications. We believe these methods will become standard tools for future research in this area. In this proposal, we seek funding only for the analysts of a newly created data set. As part of a recently completed Harvard University research project, the principal investigator designed and implemented conjoint experiments that were peer-reviewed by highly respected experts in the fields of economics and marketing research. However, a strategic decision was made to invest this original research support in obtaining the highest possible quality of data and to answer only the requisite policy questions in the initial analyses. We have now exhausted this original funding and are seeking additional support to address the important methodological issues that can be examined using these innovative stated preference survey experiments.

经济学家使用声明的偏好方法来衡量消费者从各种环境项目中获得的使用价值和非使用价值。最近，经济学家和联邦机构开始探索通过从条件估值方法转向所谓的联合方法来推广声明偏好方法的可行性。条件估值方法只向消费者提供一种选择，其价格有所不同，而联合方法则向消费者提供一个选择集，其中包含几个选择，每个选择都随着许多属性的不同而不同。联合分析的支持者认为，这可以更完整地描述从项目属性中获得的好处，并可能比传统的陈述偏好方法具有更高的统计效率和更低的财务成本。然而，几位著名的经济学家担心，在联合分析中使用的高度复杂的选择集可能会压倒消费者的认知能力，从而导致对使用和非使用价值的不可靠估计。这场争论之所以持续下去，是因为很少有关于选择集复杂性对经济效益估计的影响的研究。因此，EPA和NOAA等公共机构仍然不确定联合方法与其他非市场估值方法的相对优点。这种不确定性阻碍了在司法、监管和公共投资决策中获取和使用有关经济利益的信息。我们进入这场辩论时，对核心问题进行了一些严谨和系统的研究：选择集的复杂性如何影响消费者展示其环境便利价值的方式？为了回答这个问题，我们在一个精心设计的陈述偏好实验中改变了选择集的复杂性，然后根据实验的几个维度评估选择结果。首先，选择不一致(即犯错的倾向)如何随复杂性变化？第二，消费者的信息处理策略是否会随着选择集复杂程度的不同而发生变化，从而显著改变他们的选择(从而改变经济学家对收益的估计)？第三，消费者的个人特征如何与选择集复杂性相互作用，影响选择的一致性和信息加工策略？第四，消费者对选择集复杂性的主观评估与我们作为研究人员可以客观量化的复杂性度量之间有何关系？回答这些实质性问题将使我们能够确定当前做法的局限性，并扩大对既定偏好方法的研究范围。我们分析的核心是一个行为选择模型，该模型整合了心理学、经济学和营销学领域的几个现有文献。从这个模型出发，我们提出了一组假设，我们可以用统计方法检验这些假设，以便为上述问题提供答案。通过检验这些假设，我们将开发出识别和控制特定偏好应用中选择集复杂性的方法。我们相信，这些方法将成为未来这一领域研究的标准工具。在这项提案中，我们只为新创建的数据集的分析师寻求资金。作为哈佛大学最近完成的一个研究项目的一部分，首席研究员设计并实施了联合实验，这些实验得到了经济学和营销研究领域备受尊敬的专家的同行审查。然而，已作出战略决定，将这一原始研究支助用于获得尽可能高质量的数据，并在初步分析中只回答必要的政策问题。我们现在已经耗尽了这笔原始资金，并正在寻求更多的支持，以解决可以使用这些创新的声明偏好调查实验来审查的重要方法问题。