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When Wanting the Best Goes Right or Wrong: Distinguishing Between Adaptive and Maladaptive Maximization
Jeffrey Hughes1, Abigail A Scholer1
11 University of Waterloo, Ontario, Canada.
Personality & Social Psychology Bulletin
|September 15, 2017
Summary
Maximization research clarifies goals versus strategies. Differentiating these aspects reveals when maximization leads to negative feelings, offering new insights into decision-making processes.
Area of Science:
- Psychology
- Decision Science
- Behavioral Economics
Background:
- Conflicting conclusions exist regarding the benefits and drawbacks of maximization.
- Existing research often fails to distinguish between the goals and strategies of maximization.
Purpose of the Study:
- To differentiate between the goals (wanting the best) and strategies (e.g., alternative search) associated with maximization.
- To investigate how this differentiation impacts affective costs experienced during decision-making.
Main Methods:
- Three studies were conducted to explore the relationship between maximization goals, strategies, and affective costs.
- Study 1 examined motivational orientations (promotion focus, assessment mode) in relation to maximization goals and strategies.
- Studies 2 and 3 investigated the link between alternative search strategies and negative affective experiences (frustration, reconsideration of dismissed options).
Main Results:
- Both promotion focus and assessment mode align with the goal of wanting the best.
- Assessment mode, but not promotion focus, is linked to employing alternative search strategies.
- Alternative search strategies are associated with increased frustration and reconsideration of rejected options during decision-making.
Conclusions:
- Distinguishing between maximization goals and strategies provides a nuanced understanding of its affective consequences.
- Alternative search strategies, often employed by maximizers, can lead to negative decision-making experiences.
- This approach offers a framework to integrate and resolve conflicting findings in maximization research.
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