Unlocking the Psychology of Decision-Making: An Exploration of Prospect Theory

“Why do we make the choices we do? Why does the fear of losing $100 feel more intense than the joy of gaining $100?”

These intriguing questions lie at the heart of Prospect Theory, a groundbreaking framework developed by psychologists Amos Tversky and Daniel Kahneman. In this article, we delve into the fascinating world of decision-making under risk, challenging traditional economic models and revealing the quirks of human behavior.

Join us as we journey through reference points, biases, and real-world applications, shedding light on how our minds navigate the complex landscape of gains, losses, and uncertainty. Whether you’re a seasoned researcher or simply curious about the human psyche, Prospect Theory promises fresh insights that will forever alter the way you view decision-making.

Overview of Prospect Theory

Life choices are seldom straightforward with obvious right and wrong choices. Choice typically involve some level of risk. Behavior economists are curious about how humans make decisions when their risk. Why do we choose one prospect over another? Prior to prospect theory, the gold standard for evaluating human decision making under risk was the expected utility theory (Murphy, 2025).

Expected utility theory is an economic concept used to analyze decision-making under uncertainty. Expected utility refers to the utility of an entity or aggregate economy over a future period, given unknown circumstances. It quantifies the expected satisfaction or benefit associated with different outcomes. Expected utility theory is generally accepted as “a normative model of rational choice” (Kahneman & Tversky, 1979). Basically, individuals facing uncertainty choose actions that maximize expected utility. This involves considering all possible outcomes and their probabilities.

Daniel Kahneman and Amos Tversky explain that it is assumed that “all reasonable people would wish to obey the axioms of the theory.” Cognitive process, however, are less than perfect. Rational decision making is the ideal but certainly not a given. Having said that, most people employ rationality when making choices “most of the time” (Kahneman & Tversky, 1979).

Irrational Choice

Prospect theory does not discredit expected utility theory. Prospect theory examines several classes of “choice problems in which preferences systematically violate the axioms of expected utility theory” (Kahneman & Tversky, 1979). Basically, the problem is that humans are not always rational. In fact, we behave irrational much of the time. Dan Ariely warns that we are all far “less rational in our decision making than standard economic theory assumes. The good news is that our “irrational behaviors are neither random nor senseless—they are systematic and predictable.” Our irrationality follows a pattern. We make the “same types of mistakes over and over, because of the basic wiring of our brains” (Ariely, 2010).

Prospect theory examines some of these “systematic and predictable” irrational choices that deviate from the rational thought.

Biases in Decision-Making

Reid Hastie and Robyn Dawes explain that we discover a discrepancy when we compare basic principles of rationality with actual decision making behavior. These errors and mistakes are not to random. They occur because of “automatic and deliberate thought processes that influence how decision problems are conceptualized and how future possibilities in life are evaluated” (Hastie & Dawes, 2009).

We don’t intend to be irrational. We just are. Certain biases and functions are wired into our brains that impact decision making. These distortions have a survival value. Typically, they speed up decision making and free up expensive cognitive resources to deploy on other immediate needs.

Prospect theory examines some of these predictably irrational functions that influence decision making when the outcomes is uncertain.

The Reference Point

In the context of prospect theory, a reference point is a critical psychological concept that influences how individuals perceive and evaluate potential outcomes. Reference points serve as a baseline or anchor from which people make judgments about gains and losses.

According to prospect theory, “evaluations are relative to a baseline.” Barry Schwartz explains that any given experience “will feel positive if it’s an improvement on what came before and negative if it’s worse than what came before.” (Schwartz, 2005). This means that the same outcome can be perceived differently depending on whether it is viewed as a gain or a loss compared to the reference point.

Expectation as a Reference Point

Kahneman explains that in the context of financial outcomes, the usual “reference point is the status quo, but it can also be the outcome that you expect, or perhaps the outcome to which you feel entitled, for example, the raise or bonus that your colleagues receive.” outcomes that improve on the reference points are experienced as gains. If they are below the reference point, we experience disappointment (Kahneman, 2013).

For example, if someone’s reference point is their current salary, receiving a $5,000 bonus may be perceived as a gain if it exceeds their expectations but as a loss if they were expecting a larger bonus. This asymmetry in how gains and losses are evaluated relative to the reference point forms the basis of decision-making under uncertainty according to prospect theory.

Understanding an individual’s reference point is crucial for predicting their reactions to different scenarios and designing effective strategies for decision-making and risk management. By recognizing and manipulating reference points, businesses can influence consumer behavior and improve outcomes in various contexts such as marketing, finance, and public policy.

Loss Aversion

Loss aversion is a key concept in prospect theory that describes the tendency of individuals to prefer avoiding losses over acquiring equivalent gains. In other words, people are more sensitive to losses than gains of the same magnitude, and they are willing to take greater risks to avoid losses compared to pursuing potential gains.

Kahneman and Tversky wrote that an essential feature of prospect theory is that assignment of value to event is reliant upon “changes in wealth or welfare, rather than final states.” They explain that our perceptual apparatus is “attuned to the evaluation of changes or differences rather than the evaluation of absolute magnitude” (Kahneman & Tversky, 1979). We are especially pained by loss from a reference point, even more so than a gain of an equal amount.

Ariely warns that our aversion to loss is “a strong emotion, one that sometimes causes us to make bad decisions.” Merely thinking of losing a valued possession begins a deep mourning for the loss (Ariely, 2010).

Robert Jervis wrote: “If people are risk-averse for gains and risk-acceptant for losses, they will work to maintain what exists but take fewer chances to bring about a better situation” (Jervis, 2004).

See Loss Aversion for more on this cognitive heuristic

Endowment Effect

The endowment effect is a cognitive bias that describes the tendency of individuals to place a higher value on items they own or possess compared to identical items that they do not own. This bias leads people to overvalue objects simply because they possess them, which can influence their decision-making processes in various situations.

Jervis found through a series of experiments that “the value a person attaches to an object increases substantially when they take possession of it” (Jervis, 2004).

Ariely explains that ownership is not limited to material things. we also cling tightly to our expressed “points of view.” Once we “take ownership of an idea—whether it’s about politics or sports—what do we do? We love it perhaps more than we should. We prize it more than it is worth.” Arlie posits that we have trouble letting go of it “because we can’t stand the idea of its loss.” This refusal to check our ideas for accuracy promotes “an ideology—rigid and unyielding” (Ariely, 2010).

Weighting of Probabilities

Weighting of probabilities is a concept in behavioral economics and decision theory that refers to how individuals subjectively assess and assign importance to different probabilities when making decisions under uncertainty. In traditional economic models, people are assumed to make decisions based on objective probabilities derived from statistical data. However, research has shown that individuals often deviate from this rational approach and exhibit biases in how they perceive and weigh probabilities.

Reid Hastie and Robyn M. Dawes explain, that “people underweight probabilities when considering emotion-evoking outcomes.” Their “emotions change the shape of the prospect theory decision weight function” (Hastie & Dawes, 2009). This concept highlights that people do not always make rational decisions based solely on objective probabilities but are also influenced by their emotions and perceptions.

Key aspects of weighting probabilities include:

• Non-Linear Probability Weighting: According to prospect theory, individuals do not treat all probabilities linearly – meaning they do not view a 50% chance the same as another 50% chance. Instead, people tend to overweight low-probability events (e.g., winning the lottery) and underweight high-probability events (e.g., getting a small prize in a raffle).
• Risk Perception: The way individuals weigh probabilities can influence their perception of risk. For example, overweighting low-probability but high-impact outcomes may lead to risk-seeking behavior in certain situations where potential gains seem more attractive than the likelihood suggests.
• Framing Effects: How information is presented or framed can impact how individuals weight probabilities. People’s decisions can be influenced by whether the same probability is presented as a gain or loss relative to a reference point.
• Decision Biases: Cognitive biases such as availability heuristic or anchoring effect can also affect how individuals weight probabilities when evaluating options and making choices under uncertainty.

Understanding how individuals weight probabilities provides valuable insights for businesses seeking to optimize decision-making processes, develop effective risk management strategies, and design communication tactics that resonate with customers’ perceptions of uncertainty. By acknowledging these cognitive biases and adapting approaches accordingly, organizations can enhance their ability to address customer needs effectively while navigating complex decision environments with greater insight into human behavior patterns.

Decision Analysis Phases

In prospect theory, the designers of the theory structures the decision-making process into two phases:

• Editing: The decision maker conducts a preliminary analysis of the offered prospects, creating a simpler representation of the different prospects.
• Evaluation: In this phase the decision maker evaluates the edited prospects and choses the prospect with the highest value.

Editing Phase

The main function of the editing stage is to collect and organize information (Ze, 2019).

• Coding: This process is the evaluation of prospects using the biases previously mentioned (reference point, gains and losses, expectations, etc…)
• Combination: This process involves combining prospects that have identical outcomes.
• Segregation: Some prospects have a riskless component that is segregated from risky component in the editing phase.
• Cancellation: This process involves discarding of shared components of the different prospects.
• Simplification: This involves rounding of the probabilities or outcomes and discarding extremely unlikely outcomes.

Evaluation Phase

The editing phase creates manageable chunks of information that the decision maker can now compare value between the prospects. Kahneman and Tversky explain that “many anomalies of preferences result from the editing process” (Kahneman & Tversky, 1979).

Examples and Applications

Imagine an investor evaluating two investment options:

1. Option A: Receive $25 outright.
2. Option B: Receive $50 initially, but then give back $25.

Both options result in the same net gain of $25. However, prospect theory suggests that individuals are more likely to choose Option A (straight cash) because a single gain is perceived as more favorable than initially having more cash and then suffering a loss.

This behavior aligns with the idea that losses have a greater emotional impact than equivalent gains. Prospect theory helps explain why people often prefer certain outcomes over probabilistic ones, even when the expected value is the same.

Mention applications in fields like international relations and insurance choices.

A Few Words by Psychology Fanatic

In conclusion, prospect theory sheds light on the intricate dynamics of decision-making under risk. By emphasizing the differential valuation of gains and losses, it challenges traditional economic assumptions and provides a more nuanced understanding of human behavior. As researchers continue to explore its implications across domains, from financial choices to health-related decisions, we gain valuable insights into the complexities of the human mind. Prospect theory invites us to rethink how we frame options, consider emotions, and navigate uncertainty, ultimately enriching our understanding of the human psyche.

Last Update: April 6, 2026

Associated Concepts

• Neuroeconomics: This is a field of study that combines methods and theories from neuroscience, psychology, and economics to understand how individuals make decisions. By exploring the neural mechanisms underlying economic decision-making processes, neuroeconomics aims to shed light on topics such as risk, reward, and social interactions.
• Game Theory: A mathematical framework for analyzing strategic interactions among rational agents. Neuroeconomics uses insights from game theory to understand the neural mechanisms underlying strategic decision-making.
• Risk Assessment: This refers to a systematic process of identifying potential hazards or risks, analyzing the likelihood and severity of harm or negative outcomes associated with those hazards, and evaluating the overall risk level to determine appropriate mitigation or management strategies.
• Behavioral Economics: This field combines psychological research with economic theory to predict economic choices. It considers how mental processes and emotions affect economic decisions.
• Thinking Errors (Cognitive Biases): This refers to mistakes or inaccuracies in the way the brain processes and interprets information. These errors can occur in various cognitive processes, such as perception, attention, memory, language, reasoning, and problem-solving.
• Expected Utility Theory: This theory is an economic concept used to analyze decision-making under uncertainty.
• Value Theory: This theory is a branch of philosophy that examines the nature, origin, and evaluation of human values and moral principles. It explores questions about what constitutes intrinsic value, the source of value, and how value influences human behavior and decision-making.

References:

Ariely, Dan (2010). Predictably Irrational, Revised and Expanded Edition: The Hidden Forces That Shape Our Decisions. Harper Perennial; Revised and Expanded ed. edition. ISBN 10: 0061353248
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Hastie, Reid; Dawes, Robyn M. (2010). ‎Rational Choice in an Uncertain World: The Psychology of Judgment and Decision Making. SAGE Publications, Inc; Second edition. ISBN-10: 1412959039; APA Record: 2010-02957-000
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Jervis, Robert (2004). The Implications of Prospect Theory for Human Nature and Values. Political Psychology, 25(2). DOI: 10.1111/j.1467-9221.2004.00367.x
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Kahneman, D.; Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47, pp. 263-291. DOI: 10.2307/1914185
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Kahneman, Daniel (2013). Thinking Fast; Thinking Slow. Farrar, Straus and Giroux; 1st edition. ISBN-10: 0374533555; APA Record: 2011-26535-000
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Pan, Ze (2019). A Review of Prospect Theory. Journal of Human Resource and Sustainability Studies. DOI: 10.4236/jhrss.2019.71007
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Schwartz, Barry (2005). The Paradox of Choice: Why More Is Less. Ecco; Revised ed. edition. ISBN: 9780060005696; APA Records: 2004-13971-000
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