Decision Making Definition
Decision making is the cognitive process of assessing and considering multiple alternatives and then selecting the one that is deemed most likely to accomplish one or more objectives or goals. It is a fundamental aspect of human cognition and plays a pivotal role in various facets of life, including personal choices like voting, dining, or shopping, as well as in professional fields such as public policy, medicine, and management. The closely related concept of judgment involves the utilization of information, often gathered from diverse sources, to form evaluations or expectations. While one might assume that judgments inherently guide decisions, it’s important to recognize that this is not always the case, as decision making can involve additional factors beyond judgment.
Decision Making Background
The foundation of decision making theories can be traced back to the works of philosophers, mathematicians, and economists, who delved into the intricacies of human choices, often driven by competing goals. Early theorists, including John von Neumann, Oskar Morgenstern, and Leonard Savage, laid the groundwork for subjective expected utility theory, a particularly influential framework in decision making. This theory distinguishes between an individual’s values or utilities and their expectations or beliefs, with the central premise being the selection of an option associated with the highest expected utility. In simpler terms, decision making revolves around identifying the optimal choice.
Expected utility theory and decision theory primarily focus on normative aspects of decision making, addressing what individuals should do in ideal circumstances. In contrast, behavioral decision theory and the broader field of behavioral decision making concentrate on the descriptive aspects of decision making, seeking to understand what people actually do when forming judgments and making choices. An initial assumption was that expected utility theory, despite its roots in economic principles of rational behavior, accurately described human behavior. Departures from rational choices were expected to self-correct through learning and external influences, leading to extensive research into behavioral decision making.
This assumption spurred extensive research revealing numerous instances where individuals deviate from utility maximization, opting for choices that are not objectively the best. Consequently, expected utility theory was found to be frequently inadequate and insufficient in explaining various aspects of judgment and decision making. It fails to address how individuals select information and options for consideration, how they weigh the attributes of the available choices, and how affective and social factors influence their decisions. Furthermore, the theory does not delve into the decision-making process itself.
Herbert Simon, a cognitive scientist, introduced the concept of bounded rationality, acknowledging the finite cognitive capacity of individuals to process information. Due to these limitations, people may opt for satisficing—choosing options that are “good enough,” even if they are not the absolute best. Limited cognitive resources also lead individuals to employ shortcuts and simplification strategies known as heuristics, which typically yield satisfactory decisions but can occasionally result in errors.
Over time, behavioral decision theory has evolved to become more psychological and process-oriented. Researchers have adopted various process measures, such as verbal protocols, and introduced manipulations to gain a deeper understanding of the underlying processes involved in judgment and choice, drawing from insights derived from social and cognitive psychology.
How Judgments and Decisions Are Made
Behavioral research on judgment and decision making has documented numerous violations of normative models that were previously relied upon. The following discussion briefly reviews a few important examples.
Judgment Heuristics and Biases
Behavioral research in the field of judgment and decision making has revealed a multitude of departures from the normative models that were previously relied upon. Below, we briefly explore some key examples:
- Judgment Heuristics and Biases:Traditional theories of rational choice have assumed that individuals are generally capable of making unbiased judgments and rational decisions. However, a substantial body of research has demonstrated that people’s assessments of probabilities and values often deviate from fundamental principles of probability theory. Psychologists Amos Tversky and Daniel Kahneman, in particular, advanced three influential heuristics that play a central role in shaping intuitive judgments of probabilities, magnitudes, and frequencies:
- Representativeness Heuristic: This heuristic leads people to judge the likelihood of an event or an individual belonging to a category based on the degree of similarity between the event or individual and the prototype of that category. For instance, when assessing the likelihood that a student specializes in poetry, people evaluate the resemblance between the student and their mental image of a typical poet.
- Availability Heuristic: According to this heuristic, individuals estimate the frequency or probability of an event or characteristic based on the ease with which examples come to mind. For example, if people are asked to estimate the number of seven-letter words ending with “ing” versus the number of seven-letter words with “n” in the sixth position, their estimates tend to be influenced by the ease of recalling examples. The availability heuristic suggests that more easily recalled instances lead to higher estimates.
- Anchoring: Anchoring is the cognitive phenomenon where individuals use an initial value, or anchor, as a reference point when making judgments or decisions. Even when the anchor value is arbitrary or unrelated to the decision at hand, it can significantly influence final judgments. For example, if people are asked whether Gandhi died before or after the age of 140, their subsequent estimate of Gandhi’s age at death tends to be higher compared to when they are asked if he died before or after the age of 9. Anchoring effects have been observed in various contexts, including when people make estimates based on the last two digits of their social security numbers.
These heuristics and biases illuminate the complexities of human judgment and decision making, revealing that individuals often rely on mental shortcuts and exhibit systematic patterns of deviation from normative decision models. Understanding these cognitive processes is essential for building a more accurate and nuanced picture of how people make judgments and choices in real-world situations.
Prospect theory, developed by Daniel Kahneman and Amos Tversky, stands as a significant and comprehensive revision to address key deviations from the standard expected utility model. This theory provides a general framework to explain why people often fail to make what might seem to be the optimal choice based on traditional economic models. At the heart of prospect theory is the concept that individuals evaluate options based on whether they represent gains or losses relative to a reference point. In other words, it’s not the absolute outcome that matters most, but whether the event carries positive or negative implications for an individual’s current situation.
One common application of this concept is in the context of money. Prospect theory suggests that gaining $10,000 does not have the same psychological impact on a poor person as it does on a wealthy individual because the gain is much more significant for someone with limited financial resources.
Key Principles of Prospect Theory:
- Risk Aversion for Gains: In general, people tend to be risk-averse when it comes to gains. This means that when faced with a choice between two options—one offering a certain but smaller reward and the other offering a larger reward but with greater uncertainty—individuals are inclined to choose the option that provides a smaller but guaranteed gain.
- Risk Seeking for Losses: Conversely, prospect theory suggests that people tend to become risk-seeking or tolerant when it comes to losses. If given a choice between two options, one of which is a more certain loss and the other a larger loss but with less certainty, individuals are often inclined to select the option with the larger but riskier loss.
- Loss Aversion: One of the central insights of prospect theory is the notion of loss aversion. This principle suggests that losses have a more profound psychological impact than equivalent gains. In other words, losing $500 is psychologically more distressing than gaining $500 is pleasurable. This phenomenon is a fundamental aspect of human decision making and has been linked to behavioral biases such as the endowment effect (attaching higher value to items one owns) and the status quo bias (preferring to maintain the current state of affairs).
Prospect theory challenges the conventional economic assumption of purely rational decision making and provides a more nuanced understanding of how individuals make choices. By accounting for the psychological effects of gains and losses, as well as the inherent biases in decision making, this theory sheds light on the complexities of human behavior and choice, contributing to a richer understanding of decision processes in various contexts.
The Construction of Preferences
Since the mid-1970s, a significant body of research in decision-making has led to a growing consensus that preferences for various options are often constructed in the moment when decisions need to be made. This contrasts with the idea that preferences are static, stored in memory as a master list to be retrieved when choices arise. Instead, people tend to shape their decisions based on immediate feelings and thoughts rather than relying on deeply ingrained, pre-existing beliefs to guide their choices. This dynamic process makes choices highly sensitive to factors such as how options are framed, the context in which choices are made, and the methods used to elicit preferences.
- The way options are framed can significantly influence preferences. For example, presenting options as potential losses rather than gains tends to make people more risk-seeking in their preferences.
- Framing can also affect how people evaluate the desirability of a product or choice. For instance, describing ground beef as “80% lean” is more appealing to consumers than framing it as containing “20% fat,” even though both convey the same information about the meat’s quality.
Choice Context and Set Configuration:
- The context in which choices are presented plays a crucial role in shaping preferences. Introducing an asymmetrically dominated option, one that is clearly less attractive than others, can increase the appeal of the dominating option in the set.
- The presence of a “compromise” or middle option often influences preferences. People tend to favor options that lie between extreme choices when making decisions.
Preference Elicitation Tasks:
- The method used to elicit preferences can yield different results. For example, performing a matching task, where individuals are asked to find a value that makes two options equally attractive, can lead to distinct preferences compared to a simple choice task.
- Ratings or evaluations of individual options can produce different preferences compared to tasks that involve choosing between options or jointly evaluating them.
These findings underscore the dynamic and context-dependent nature of preferences. They highlight that preferences are not static but rather constructed in the decision-making process itself. This understanding has profound implications for fields such as marketing, economics, and psychology, as it challenges the traditional notion that preferences are fixed and suggests that how choices are presented and framed can significantly impact the decisions people ultimately make.
Current Directions in Decision Research
As the question of whether expected utility model adequately describes decision making has been largely resolved, decision researchers have tried to gain a better understanding of how decisions are actually made, often using various process measures and task manipulations. Furthermore, researchers have examined a wider range of judgment and decision-making dimensions and have addressed topics that were previously regarded as the domain of other fields, such as social and cognitive psychology and business administration.
Traditionally, decision research primarily focused on the outcomes of decisions, such as which option individuals chose. However, a shift in understanding has highlighted the importance of examining decision processes. These processes offer valuable insights into decision making because they can be influenced by various task and option variations that may not always directly impact the final decision outcomes. It was initially assumed that decision makers applied specific decision rules, such as forming an evaluation of each option by summing the positive aspects and subtracting the negative aspects (weighted additive or compensatory model) or by selecting essential decision criteria and making choices based on whether options met certain cutoffs in those criteria (conjunctive rule or lexicographic decision rules).
However, in line with the concept of constructed preferences, subsequent research has demonstrated that decision makers often combine fragments of various decision rules. For example, they may begin by eliminating options that fail to meet specific standards and then use compensatory rules that involve adding positives and subtracting negatives to evaluate the remaining options.
Early process-oriented decision research relied heavily on process measures. These measures included factors such as response latencies (the time it takes to make a decision), the percentage of intradimensional (comparisons within the same attribute, like comparing the size of two products) versus inter-dimensional (comparisons across different attributes, like comparing the size and price of two products) comparisons, and verbal protocols (participants verbalizing their thought processes during decision-making). While these measures offer rich and valuable data, questions can arise about whether the behaviors and responses captured genuinely represent naturally occurring decision processes.
A complementary approach in decision research is to manipulate task conditions (e.g., introducing cognitive load or time pressure), manipulate stimuli (changing the attributes or characteristics of options), and consider individual differences. These methods allow researchers to infer the underlying decision processes and identify factors that moderate the observed decision outcomes.
By examining decision processes alongside decision outcomes, researchers gain a more comprehensive understanding of how choices are made. This holistic approach helps uncover the intricacies of decision-making, offering insights into the cognitive mechanisms at play, the impact of external factors, and individual variations in decision processes. Ultimately, this contributes to a more nuanced and accurate depiction of the decision-making process in various contexts.
The Role of Affect in Decision Making
Traditional decision research has predominantly focused on the objective evaluation of options based on factors like the probability of success and potential payoff. However, a growing recognition in the field acknowledges that decisions are often significantly influenced by the affective reactions individuals have toward those options. Affect, in this context, refers to the emotional response triggered by the perceived “goodness” or attractiveness of various choices. These emotional reactions can arise automatically, often without conscious thought or deliberation. It’s increasingly suggested that these automatic, affective reactions serve as primary drivers of judgments and decisions, with conscious and deliberate reasoning serving more as post hoc explanations for these decisions.
Researchers have employed a wide range of methodologies to explore the role, prominence, and speed of affective reactions in response to decision-related stimuli. Some of these methods include:
- Subliminal Priming: Subliminal presentation of emotional cues or images can subtly influence decision making. Even when participants are not consciously aware of these stimuli, they can still affect their choices.
- Observation of Patients: Studies involving individuals with damage to brain areas responsible for affective processing have shed light on the importance of emotions in decision making. Patients with impaired emotional processing often exhibit unusual and less adaptive decision behaviors.
- Mood Manipulation: Experimenters have explored how inducing positive or negative moods in participants can impact their decision-making processes. A person’s current emotional state can significantly influence the choices they make.
The recognition of the role of affect in decision making has broad implications across various fields, including psychology, economics, and marketing. It highlights the complex interplay between emotion and cognition in shaping human choices. Understanding how affective reactions influence decisions can help researchers and practitioners develop a more comprehensive understanding of why people make the choices they do and design interventions and strategies that consider the emotional undercurrents of decision making.
The Two-System View of Judgment and Decision Making
Within the realm of judgment and decision making, there is a recognized division between two broad systems of cognitive processing. These systems shape the way individuals evaluate options and make choices:
- Automatic, Affective Reactions: This first system encompasses judgments and decisions made intuitively and automatically, often without the need for deliberate evaluation or conscious thought. Under this system, individuals rely on emotional and immediate reactions to assess options. These automatic, affective responses are believed to be a fundamental aspect of many, and possibly most, judgments and decisions. They can heavily influence choices, serving as the initial drivers of decision making.
- Deliberate, Reason-Based Processes: The second system involves more conscious, deliberate, and reasoned evaluation of options and their attributes. Unlike the automatic system, which operates rapidly and intuitively, this system engages slower, more reflective thinking. Deliberate evaluations play a more significant role in the final choice selection process.
It is essential to note that both intuitive, automatic responses and deliberate evaluations have their place in decision making. Automatic reactions are often the initial responses to decision stimuli and can have a substantial impact on judgments and choices. However, deliberate evaluations, driven by careful consideration of reasons for and against options, tend to play a more prominent role in the final selection of choices.
This two-system view helps explain various phenomena in decision making, including choice anomalies such as the asymmetric dominance and compromise effects. These anomalies can be challenging to account for based solely on value maximization or by assuming that decisions are exclusively automatic and lack consideration of attributes or the relationships among options. Instead, this framework recognizes that both intuitive and reasoned processes interact to shape the complexities of human decision making.
Social and Cultural Aspects of Decision Making
In the realm of decision making, researchers have recognized the significant influence of social and cultural factors, as well as individual differences, on the process and outcomes of choices. Here are some key insights into these dimensions:
Social Factors in Decision Making:
- Conformity: Conformity, or the tendency to align one’s choices with those of a group or majority, has a notable impact on decision making. While conformity may seem straightforward, it plays a crucial role in shaping individual decisions, often leading individuals to make choices that align with social norms or the preferences of others.
- Accountability and Justification: Social conditions, such as being accountable for one’s decisions and having to justify them to others, can moderate and potentially reduce susceptibility to various judgment and decision errors. Researchers have explored how accountability mechanisms can influence decision performance and help mitigate certain errors, particularly those stemming from limited effort.
- Social Incentives: Similar to monetary compensation for performance, social incentives have been investigated in the context of decision making. Research suggests that while social incentives can have a positive impact on decision performance, their effects are often limited. These incentives may be more effective in reducing errors related to effort than in fundamentally altering decision outcomes.
Cultural Aspects of Decision Making:
- Cross-Cultural Differences: Researchers have long been interested in the impact of culture on decision performance. Initially, studies focused on differences between individualistic societies (e.g., the United States and Western Europe) and collectivist societies (e.g., Asian cultures). For instance, research indicated that collectivist cultures might be more susceptible to overconfidence bias.
- Situational Sensitivity: Recent research suggests that cross-cultural differences in judgment and decision making may be less rigid and more sensitive to various situational factors than previously assumed. While cultural background undoubtedly shapes decision tendencies, contextual influences can moderate these effects, leading to more nuanced and complex outcomes.
In summary, decision making is not solely an individual endeavor but is deeply influenced by social dynamics and cultural contexts. Social factors like conformity, accountability, and social incentives can impact how decisions are made and their outcomes. Additionally, the role of culture in decision making is a multifaceted one, with cultural backgrounds interacting with situational factors to shape choices. Understanding these social and cultural dimensions is crucial for comprehending the complexities of human decision making across diverse contexts and populations.
Decision Making Research in Applied Fields
The landscape of decision-making research has evolved, with a notable shift of behavioral decision researchers from psychology departments to business schools. This transition reflects the increasing impact of decision research on various applied fields, including marketing, organizational behavior, and behavioral economics. Here are some key developments in decision research within applied contexts:
1. Consumer Decision Making: Over the past few decades, a significant body of behavioral decision research has been dedicated to understanding consumer decision making. Researchers have explored topics related to consumer choices, preferences, and the psychological factors that influence purchasing decisions. This research has had a substantial impact on marketing strategies and consumer behavior models.
2. Bargaining and Fairness: Behavioral decision research has delved into the realms of bargaining and fairness. Studies in this area have examined how individuals negotiate and make decisions in situations involving fairness considerations. Insights from this research have practical applications in various contexts, including business negotiations and conflict resolution.
3. Behavioral Game Theory: Behavioral decision researchers have made significant contributions to the field of game theory, focusing on how people make decisions in strategic interactions. This research has expanded our understanding of human behavior in competitive scenarios and has practical applications in economics, politics, and social interactions.
4. Behavioral Economics Integration: The field of economics, which traditionally emphasized rational decision making, has increasingly recognized the importance of systematic deviations from rationality. Behavioral economics, an evolving subfield, has incorporated descriptive aspects of decision making, often derived from research conducted by behavioral decision researchers. This integration has led to a deeper understanding of choice, value assessments, and issues related to discrimination in economic models.
In summary, the influence of decision-making research has extended well beyond the confines of traditional psychology departments. Researchers in business schools and applied fields have embraced the insights gained from behavioral decision research, applying them to real-world scenarios and addressing practical challenges in various domains. This interdisciplinary approach has enriched our understanding of decision making and its impact on human behavior and society as a whole.
- Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of choice under risk. Econometrica, 47(2), 263-291.
- Savage, L. J. (1954). Foundations of statistics. Oxford, UK: Wiley.
- Simon, H. A. (1957). Models of man: Social and rational. Oxford, UK: Wiley.
- Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4151), 1124-1131.
- Von Neumann, J., & Morgenstern, O. (1941). Theory of games and economic behavior (2nd ed.). Princeton, NJ: Princeton University Press.