Irrational Escalation
The phenomenon where people continue a failing course of action due to the amount of resources already invested. Important for recognizing and mitigating biased decision-making.
The phenomenon where people continue a failing course of action due to the amount of resources already invested. Important for recognizing and mitigating biased decision-making.
The ability to influence others' behavior by offering positive incentives or rewards, commonly used in organizational and social contexts. Crucial for understanding dynamics of motivation and influence in team and organizational settings.
A cognitive bias where people ignore general statistical information in favor of specific information. Critical for designers to use general statistical information to improve decision-making accuracy and avoid bias.
A cognitive bias where people ignore the relevance of sample size in making judgments, often leading to erroneous conclusions. Crucial for designers to account for appropriate sample sizes in research and analysis.
The process of encoding sensory input that has particular meaning or can be applied to a context, enabling deeper processing and memory retention. Important for understanding how information is processed and stored, enhancing design of educational content.
The economic theory that suggests limited availability of a resource increases its value, influencing decision-making and behavior. Important for creating urgency and increasing perceived value in marketing.
A pricing strategy that offers a middle option with substantial value at a moderate price, often perceived as the best deal by users. Useful for driving sales by presenting a balanced choice that appears more attractive relative to higher and lower-priced options.
A cognitive approach where information is processed at a surface level, focusing on basic features rather than deeper meaning, often leading to poorer memory retention. Important for designing educational and informational content that encourages deeper processing and understanding.
A type of bias that occurs when the observer's expectations or beliefs influence their interpretation of what they are observing, including experimental outcomes. Essential for ensuring the accuracy and reliability of research and data collection.
The tendency to overvalue new innovations and technologies while undervaluing existing or traditional approaches. Important for balanced decision-making and avoiding unnecessary risks in adopting new technologies.
A tendency for respondents to answer questions in a manner that is not truthful or accurate, often influenced by social desirability or survey design. Important for understanding and mitigating biases in survey and research data.
A cognitive process where ideas are brought together to find a single, best solution to a problem. Important for problem-solving and decision-making in design processes.
A sales technique used to uncover a prospect's pain points through a series of targeted questions. Important for understanding customer needs and driving effective sales conversations.