Prospect theory, developed by Daniel Kahneman and Amos Tversky in 1977, is a behavioral economic theory that describes how people make decisions under risk and uncertainty. Unlike traditional utility theory, which assumes that individuals act rationally to maximize expected utility, prospect theory suggests that people value gains and losses differently, leading to decisions that deviate from rationality. The theory introduces the concept of a reference point, from which gains and losses are evaluated, and posits that individuals are generally loss-averse, meaning they experience losses more intensely than gains of the same magnitude Kahneman, 1977.

A key aspect of prospect theory is its explanation of risk behavior. When faced with potential gains, individuals tend to be risk-averse, preferring certain outcomes over gambles with higher or equal expected value. Conversely, when confronted with potential losses, individuals become risk-seeking, willing to engage in riskier behavior to avoid losses. This shift in risk preference based on the framing of outcomes as gains or losses has been supported by empirical evidence across various fields, including political decision-making and digital health technology adoption Vis, 2011; Khan, 2021.

Prospect theory has significant implications for decision-making processes in multiple domains. For instance, in tourism, it helps explain why travelers might choose certain destinations or activities based on perceived gains or losses relative to their reference points. Similarly, in power network planning, the theory aids in understanding how decision-makers evaluate different planning schemes under uncertainty, incorporating their risk preferences and subjective biases Lin, 2023; Sha, 2014. By accounting for these psychological factors, prospect theory provides a more accurate model of human behavior than traditional economic theories.

In summary, prospect theory offers a nuanced understanding of decision-making under risk by highlighting the importance of reference points, loss aversion, and the differential treatment of gains and losses. It has broad applications across various fields, providing insights that challenge the assumptions of traditional utility theory.

A science AI for researchers

The AI research tool by scienceOS offers scientific answers, features a multi-PDF chat and comes with an integrated reference manager.

Ask scientific questions and chat with 220 Mio papers – try scienceOS for free.

Upload up to eight PDFs per chat and ask multiple files at once.

About scienceOS


The AI research tool for scientists with high standards and little time.

Used by researchers at

Used by researchers at

A science AI for researchers

The AI research tool scienceOS provides scientific answers, creates tables and diagrams, and draws citation networks.

Used by researchers at