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Dynamic Goal Choice when Environment Demands Exceed Individual’s Capacity: Scaling up the Multiple-Goal Pursuit Model

Li, Xiaofei
http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1493389920717575

Abstract Details

2017, Doctor of Philosophy (PhD), Ohio University, Industrial/Organizational Psychology (Arts and Sciences).
Navigating the complexities of life where one must managing multiple goals, where one’s status vis-a-vie those goals are constantly changing, and where limited resources undermines the ability to pursue all of one’s goals simultaneously, creates a thorny problem for individuals as well as psychologists trying to understand how individuals manage this process. Recently researchers have started to use computational modeling to better understand the dynamic processes involved in multiple-goal pursuit. However most models and research are limited in a way that (a) they have assumed that people use a normative decision strategy, and (b) focused on the pursuit of two goals. Whereas in real life people often need to juggle more than two goals, decision-making literatures suggested that people may not always adopt the normative strategy. The present study aims to advance our knowledge by (a) scaling up the existing model on multiple-goal pursuit to more than two goals, (b) proposing a two-stage decision mechanism involving a range of heuristic to analytic strategies, and (c) developing nine computational models to represent the possible ordering of these strategies over time to explain individuals’ behavior. I conducted an experiment to test the models’ predictions. The results showed that individuals tended to use more heuristic strategies compared to more analytic strategies, and tended to switch from a more heuristic to more analytic strategy if they switched. The decision strategy represented in a model that represented people as starting with the simplest heuristic strategy (i.e., decide based on goal with the largest discrepancy) and then switching to the least complicated analytic strategy (i.e., decide based on goal discrepancy weighted by goal importance) received the strongest support. Theoretical and practical implications, as well as future directions, are discussed.
Jeffrey Vancouver (Advisor)
Claudia Gonzalez-Vallejo (Committee Member)
Ryan Johnson (Committee Member)
Bruce Carlson (Committee Member)
Jim Zhu (Committee Member)
111 p.
Psychology
multiple goals; dynamic self-regulation; computational modeling; decision making

Recommended Citations

Citations

  • Li, X. (2017). Dynamic Goal Choice when Environment Demands Exceed Individual’s Capacity: Scaling up the Multiple-Goal Pursuit Model [Doctoral dissertation, Ohio University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1493389920717575

    APA Style (7th edition)

  • Li, Xiaofei. Dynamic Goal Choice when Environment Demands Exceed Individual’s Capacity: Scaling up the Multiple-Goal Pursuit Model. 2017. Ohio University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1493389920717575.

    MLA Style (8th edition)

  • Li, Xiaofei. "Dynamic Goal Choice when Environment Demands Exceed Individual’s Capacity: Scaling up the Multiple-Goal Pursuit Model." Doctoral dissertation, Ohio University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1493389920717575

    Chicago Manual of Style (17th edition)

ohiou1493389920717575
247
© 2017, all rights reserved.
This open access ETD is published by Ohio University and OhioLINK.