Decision Making: Factors that Influence Decision Making, Heuristics Used, and Decision Outcomes (2024)

Every day, people are inundated with decisions, big and small. Understanding how people arrive at their choices is an area of cognitive psychology that has received attention. Theories have been generated to explain how people make decisions, and what types of factors influence decision making in the present and future. In addition, heuristics have been researched to understand the decision making process.

Several factors influence decision making. These factors, including past experience (Juliusson, Karlsson, & Gӓrling, 2005), cognitive biases (Stanovich & West, 2008), age and individual differences (Bruin, Parker, & Fischoff, 2007), belief in personal relevance (Acevedo, & Krueger, 2004), and an escalation of commitment, influence what choices people make. Understanding the factors that influence decision making process is important to understanding what decisions are made. That is, the factors that influence the process may impact the outcomes.

Heuristics serve as a framework in which satisfactory decisions are made quickly and with ease (Shah & Oppenheimer, 2008). Many types of heuristics have been developed to explain the decision making process; essentially, individuals work to reduce the effort they need to expend in making decisions and heuristics offer individuals a general guide to follow, thereby reducing the effort they must disburse. Together, heuristics and factors influencing decision making are a significant aspect of critical thinking (West, Toplak, & Stanovich, 2008). There is some indication that this can be taught, which benefits those learning how to make appropriate and the best decisions in various situations (Nokes &Hacker, 2007).

People make decisions about many things. They make political decisions; personal decisions, including medical choices, romantic decisions, and career decisions; and financial decisions, which may also include some of the other kinds of decisions and judgments. Quite often, the decision making process is fairly specific to the decision being made. Some choices are simple and seem straight forward, while others are complex and require a multi-step approach to making the decisions.

The present paper will address decision making, in the context of types of decisions people make, factors that influence decision making, several heuristics commonly researched and utilized in the process of decision making. Further, the paper will explore what happens after the decision is made, as well as how present decisions impact future behavior and decision making. Finally, summary comments will be offered, with implications for future research and practical application of teaching decision making skills in teens.

Factors that Influence Decision Making

There are several important factors that influence decision making. Significant factors include past experiences, a variety of cognitive biases, an escalation of commitment and sunk outcomes, individual differences, including age and socioeconomic status, and a belief in personal relevance. These things all impact the decision making process and the decisions made.

Past experiences can impact future decision making. Juliusson, Karlsson, and Garling (2005) indicated past decisions influence the decisions people make in the future. It stands to reason that when something positive results from a decision, people are more likely to decide in a similar way, given a similar situation. On the other hand, people tend to avoid repeating past mistakes (Sagi, & Friedland, 2007). This is significant to the extent that future decisions made based on past experiences are not necessarily the best decisions. In financial decision making, highly successful people do not make investment decisions based on past sunk outcomes, rather by examining choices with no regard for past experiences; this approach conflicts with what one may expect (Juliusson et al., 2005).

In addition to past experiences, there are several cognitive biases that influence decision making. Cognitive biases are thinking patterns based on observations and generalizations that may lead to memory errors, inaccurate judgments, and faulty logic (Evans, Barston, & Pollard, 1983; West, Toplak, & Stanovich, 2008). Cognitive biases include, but are not limited to: belief bias, the over dependence on prior knowledge in arriving at decisions; hindsight bias, people tend to readily explain an event as inevitable, once it has happened; omission bias, generally, people have a propensity to omit information perceived as risky; and confirmation bias, in which people observe what they expect in observations (Marsh, & Hanlon, 2007; Nestler. & von Collani, 2008; Stanovich & West, 2008; see also West et al., 2008).

In decision making, cognitive biases influence people by causing them to over rely or lend more credence to expected observations and previous knowledge, while dismissing information or observations that are perceived as uncertain, without looking at the bigger picture. While this influence may lead to poor decisions sometimes, the cognitive biases enable individuals to make efficient decisions with assistance of heuristics (Shah & Oppenheimer, 2008).

In addition to past experiences and cognitive biases, decision making may be influenced by an escalation of commitment and sunk outcomes, which are unrecoverable costs. Juliusson, Karlsson, and Garling (2005) concluded people make decisions based on an irrational escalation of commitment, that is, individuals invest larger amounts of time, money, and effort into a decision to which they feel committed; further, people will tend to continue to make risky decisions when they feel responsible for the sunk costs, time, money, and effort spent on a project. As a result, decision making may at times be influenced by ‘how far in the hole’ the individual feels he or she is (Juliusson et al., 2005).

Some individual differences may also influence decision making. Research has indicated that age, socioeconomic status (SES), and cognitive abilities influences decision making (de Bruin, Parker, & Fischoff, 2007; Finucane, Mertz, Slovic, & Schmidt, 2005). Finucane et al. established a significant difference in decision making across age; that is, as cognitive functions decline as a result of age, decision making performance may decline as well. In addition, older people may be more overconfident regarding their ability to make decisions, which inhibits their ability to apply strategies (de Bruin et al., 2007). Finally, with respect to age, there is evidence to support the notion that older adults prefer fewer choices than younger adults (Reed, Mikels, & Simon, 2008).

Age is only one individual difference that influences decision making. According to de Bruin et al. (2007), people in lower SES groups may have less access to education and resources, which may make them more susceptible to experiencing negative life events, often beyond their control; as a result, low SES individuals may make poorer decisions, based on past decisions.

Over and above past experiences, cognitive biases, and individual differences; another influence on decision making is the belief in personal relevance. When people believe what they decide matters, they are more likely to make a decision. Acevedo and Krueger (2004) examined individuals’ voting patterns, and concluded that people will vote more readily when they believe their opinion is indicative of the attitudes of the general population, as well as when they have a regard for their own importance in the outcomes. People vote when they believe their vote counts. Acevedo and Krueger pointed out this voting phenomenon is ironic; when more people vote, the individual votes count less, in electoral math.Continued on Next Page »

Abraham, C., & Sheeran, P. (2003). Acting on intentions: The role of anticipated regret. British Journal of Social Psychology, 42, 495-511.

Acevedo, M., & Krueger, JI. (2004). Two egocentric sources of the decision to vote: The voter’s illusion and the belief in personal relevance. Political Psychology, 25(1), 115-134. DOI: 10.1111/j.1467-9221.2004.00359.x.

Botti, S., & Iyengar, S.S. (2004). The psychological pleasure and pain of choosing: When people prefer choosing at the cost of subsequent outcome satisfaction. Journal of Personality and Social Psychology, 87(3), 312-326. DOI: 10.1037/0022-3514.87.3.312.

de Bruin, W.B., Parker, A.M., & Fischhoff, B. (2007). Individual differences in adult decision-making competence. Journal of Personality and Social Psychology, 92(5), 938-956. DOI: 10.1037/0022-3514.92.5.938.

Epley, N., & Gilovich, T. (2006). The anchoring-and-adjustment heuristic. Psychological Science, 17(4), 311-318. DOI: 10.1111/j.1467-9280.2006.01704.x.

Evans, J.ST., Barston, J.L., & Pollard, P. (1983). On the conflict between logic and belief in syllogistic reasoning. Memory & Cognition, 11(3), 295-306.

Finucane, M.L., Mertz, C.K., Slovic, P. & Schmidt, E.S. (2005). Task complexity and older adults’ decision-making competence. Psychology and Aging, 20(1), 71-84. DOI: 10.1037/0882-7974.20.1.71.

Gilbert, D.T., & Ebert, J.E.J. (2002). Decisions and revisions: The affective forecasting of changeable outcomes. Journal of Personality and Social Psychology, 82(4), 503-514. DOI: 10.1037/0022-3514.82.4.503.

Goldstein, D.G., & Gigerenzer, G. (2002). Models of ecological rationality: The recognition heuristic. Psychological Review, 109(1), 75-90. DOI: 10.1037/0033-295X.109.1.75.

Hilbig, B.E., & Pohl, R.F. (2008). Recognition users of the recognition heuristic. Experimental Psychology, 55(6), 394-401. DOI: 10.1027/1618-3169.55.6.394.

Jullisson, E.A., Karlsson, N., Garling, T. (2005). Weighing the past and the future in decision making. European Journal of Cognitive Psychology, 17(4), 561-575. DOI: 10.1080/09541440440000159.

Kim, S., Healy, K., Goldstein, D., Hasher, L., & Wiprzycka, U.J. (2008). Age differences in choice satisfaction: A positivity effect in decision making. Psychology and Aging, 23(1), 33-38. DOI: 10.1037/0882-7974.23.1.33.

Krantz, D.H., & Kunreuther, H.C. (2007). Goals and plans in decision making. Judgment and Decision Making, 2(3), 137-168.

Marsh, D.M., & Hanlon, T.J. (2007). Seeing what we want to see: Confirmation biases in animal behavior research. Ethology, 113(11), 1089-1098. DOI: 10.1111/j.1439-0310.2007.01406.x.

McKelvie, S.J. (2000). Quantifying the availability heuristic with famous names. North American Journal of Psychology, 2(2), 347-357.

Nestler, S. & von Collani, G. (2008). Hindsight bias, conjunctive explanations and causal attribution. Social Cognition, 26(4), 482-493.

Nokes, J.D., Dole, J.A., & Hacker, D.J. (2007). Teaching high school students to use heuristics while reading historical texts. Journal of Educational Psychology, 99(3), 492-504. DOI: 10.1037/0022-0663.99.3.492.

Pachur, T, & Hertwig, R. (2006). On the psychology of the recognition heuristic: Retrieval primacy as a key determinant of its use. Journal of Experimental Psychology, Learning, Memory, and Cognition, 32(5), 983-1002. DOI: 10.1037/0278-7393.32.5.983.

Redelmeier, D.A. (2005). The cognitive psychology of missed diagnosis. Annals of Internal Medicine, 142(2), 115-120.

Reed, A.E., Mikels, J.A., & Simon, K.I. (2008). Older adults prefer less choice than young adults. Psychology and Aging, 23(3), 671-675. DOI: 10.1037/a0012772.

Sagi, A., & Friedland, N. (2007). The cost of richness: The effect of the size and diversity of decision sets on post-decision regret. Journal of Personality and Social Psychology, 93(4), 515-524. DOI: 10.1037/0022-3514.93.4.515.

Shah, A.K., & Oppenheimer, D.M. (2008).Heuristics made easy: An effort-reduction framework. Psychological Bulletin, 134(2), 207-222. DOI: 1.1037/0033-2909.134.2.207.

Stanovich, K.E., & West, R.F. (2008). On the relative independence of thinking biases and cognitive ability. Journal of Personality and Social Psychology, 94(4), 672-695. DOI: 10.1037/0022-3514.94.4.672.

West, R.F., Toplak, M.E., & Stanovich, K.E. (2008). Heuristics and biases as measures of critical thinking: Associations with cognitive ability and thinking dispositions. Journal of Educational Psychology, 100(4), 930-941. DOI: 10.1037/a0012842.

Wester, S.R., Christianson, H.F., Fouad, N.A., Santiago-Rivera, A.L. (2008). Information processing as problem solving: A collaborative approach to dealing with students exhibiting insufficient competence. Training and Education in Professional Psychology, 2(4), 193-201. DOI: 10.1037/1931-3918.2.4.193.

Wood, S.L. (2001). Remote purchase environments: The influence of return policy leniency on two-stage decision process. Journal of Marketing Research, 38(2), 157-169.

Save Citation »(Works with EndNote, ProCite, & Reference Manager)

Cindy Dietrich is pursuing her PhD in Educational Psychology at Walden University in Minneapolis, MN.

From the Inquiries Journal Blog

Related Reading

Suggested Reading from Inquiries Journal

Page Top Next Page »