Modeling the Underlying Dynamic Processes in Motivation and Decision Making: A Parsimonious Self-Regulatory Approach

对动机和决策中的潜在动态过程进行建模：一种简约的自我调节方法

• 批准号: 0851764
• 负责人: Jeffrey Vancouver
• 金额: $ 40.81万
• 依托单位: Ohio University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2012-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0851764&HistoricalAwards=false
• 关键词: Modeling; Underlying; Dynamic; Processes; Motivation

"This award is funded under the American Recovery and Reinvestment Act of 2009(Public Law 111-5)."Most formal models of decision-making treat it as a static process (i.e., how the current state of some set of variables affects the probability of a particular choice). This approach ignored the fact that each day individuals are faced with numerous decisions regarding the allocation of resources (e.g., time, attention, and effort) across competing tasks in order to meet or maintain many goals. It also ignores that fact that, over time, circumstances (both internal and external) change and learning occurs both of which may result in changes in the choices one makes to attain or maintain one?s goals. Finally, contemporary models of decision making are largely silent with regards to the underlying psychological and information processes that are responsible for observed decision patterns over time. Under this grant, a group of researchers composed of an engineer and three psychologists use a simple information processing structure ? the weighted difference model common in engineering control theories ? to explain numerous decision-making, motivational, and economic phenomena. For example, this structure is used to construct models that explain why 1) individuals work longer on days when they are paid a relatively lower wage; 2) beliefs in one?s capacities to perform are sometimes negatively and sometimes positively related to the resources one allocates to the task; 3) individuals tend to switch back and forth between two tasks with the same deadline, but then focus on only one as the deadline draws near; 4) individuals change their risk attitudes when making choices as they approach their goal, and 5) individuals? change their choices over time despite no change in the options or their attributes. Several empirical studies are designed to test the proposed models. If found valid, the research will demonstrate that models based on this structure not only allow predictions over time (i.e., are dynamic), but also are consistent with empirically confirmed elements of well-accepted static models of decision making and motivation. Moreover, they integrate aspects of economic, psychomotor, and learning models, providing a general, comprehensive, yet parsimonious approach to understanding human behavior in naturalistic contexts.

“该奖项是根据2009年《美国复苏和再投资法案》(公法111-5)提供资金的。”大多数正式的决策模型将其视为一个静态过程(即，某些变量的当前状态如何影响特定选择的概率)。这种方法忽略了这样一个事实，即个人每天都面临着关于在相互竞争的任务之间分配资源(例如，时间、注意力和努力)的众多决定，以实现或保持许多目标。它也忽略了这样一个事实，随着时间的推移，环境(内部和外部)变化和学习发生，这两者都可能导致一个人为实现或保持S的目标而做出的选择发生变化。最后，当代的决策模型在很大程度上对潜在的心理和信息过程保持沉默，这些过程是随着时间的推移而观察到的决策模式的责任。在这笔拨款下，一个由一名工程师和三名心理学家组成的研究小组使用了一个简单的信息处理结构？工程控制理论中常见的加权差分模型？解释许多决策、激励和经济现象。例如，这种结构被用来构建模型，解释为什么1)当工资相对较低时，个人工作时间更长；2)对一种信念的信念？S的执行能力有时与分配给任务的资源呈负相关，有时呈正相关；3)个人倾向于在两项具有相同截止日期的任务之间来回切换，但随着截止日期的临近，他们只专注于一项；4)在接近目标时，个人在做出选择时改变了他们的风险态度；以及5)个人？尽管选项或其属性没有变化，但随着时间的推移，他们的选择会发生变化。设计了几个实证研究来检验所提出的模型。如果被发现是有效的，研究将证明，基于这种结构的模型不仅允许随着时间的推移进行预测(即，是动态的)，而且与被广泛接受的决策制定和动机的静态模型的经验确认的要素一致。此外，它们整合了经济学、精神运动学和学习模型的各个方面，为理解自然主义背景下的人类行为提供了一种一般的、全面的、但又简约的方法。