CAREER: Identification and integration of persistent behavioral biases into online search and purchase models

离散选择模型是许多领域实证分析的支柱。这些模型基于随机效用最大化理论，通常需要观察基本属性，包括稳定和传递偏好。行为经济学家最近的研究表明，这些属性可能并不适用于所有的决策环境，如果不能正确解释这些和其他行为偏差，可能会导致预测准确性差。本CAREER建议的目标是：1）将行为偏差整合到离散选择模型中，以增强我们对个人和公司决策的基础知识; 2）调查在当前市场条件下发现的重要行为偏差是否在未来市场条件下持续存在; 3）发展和验证个人，搜索和购买行为的理论;以及，4）基于国家规定的基于问题的学习技术，为格鲁吉亚高中教师开发概率模块，该技术使用代表实践中遇到的工程问题的数据集。研究结果将在航空业中应用和测试，这为在各种市场条件下测试行为理论提供了理想的条件。 这是由于在一个具有灵活能力的发达行业中，能够跟踪菜单和旅行者做出的决定。 该提案创造性地整合了来自多个在线来源的数据，并与航空业进行的在线实验进行了补充。分析自然发生的在线市场的大量数据的能力提供了发现新的经验见解的机会，这将推动理论模型的发展。从这个职业生涯的发展建议将明确整合个人，搜索和购买行为与公司决策。这种方法的结果是在一个理论基础，是独特的，从其他研究人员，并揭示了需求和行为偏差的假设是不平凡的，并可能导致预测相反的经典模型预测。最重要的更广泛影响是改变在线市场性质的潜力，使其与客户更具互动性，这将增加企业的利润，并为客户提供更好的产品和服务。

Discrete choice models are the backbone of empirical analysis in many fields. These models are grounded in random utility maximization theory and generally require that fundamental properties, including stable and transitive preferences, be observed. Recent work by behavioral economists suggests that these properties may not be valid in all decision making contexts, and that failure to properly account for these and other behavioral biases may lead to poor forecasting accuracy. The objectives of this CAREER proposal are to: 1) integrate behavioral biases into discrete choice models to enhance our fundamental knowledge of individual and firm decision making; 2) investigate whether behavioral biases found to be important in current market conditions persist in future market conditions; 3) develop and validate theories of individuals, search and purchase behaviors; and, 4) develop probability modules for Georgia high school teachers based on state-mandated problem-based learning techniques that use datasets representative of engineering problems encountered in practice.The research findings will be applied and tested in the airline industry, which affords ideal conditions for testing behavioral theories under a wide variety of market conditions. This is due to the ability to both track menus and decisions made by travelers in a developed industry that has flexible capacity. This proposal creatively integrates data from multiple online sources and complements this with online experiments conducted with the airline industry. The ability to analyze large volumes of data from naturally occurring online markets provides the opportunity to uncover new empirical insights that will drive the development of theoretical models.The developments from this CAREER proposal will explicitly integrate individuals, search and purchase behaviors with firm decision-making. This approach results in a theoretical foundation that is unique from that of other researchers and reveals that demand and behavioral bias assumptions are not trivial and can result in forecasts opposite those predicted by classic models. The most important broader impact is the potential to change the nature of online markets to make them more interactive with customers, which will result in both increased profits for firms as well as better product and service offerings for customers.