The representativeness heuristic at work in decision-making: building blocks and individual-level cognitive and behavioral factors

Abstract

PurposeThis paper aims to develop a conceptual framework on how the representativeness heuristic operates in the decision-making process. Specifically, the authors unbundle representativeness into its building blocks: search rule, stopping rule and decision rule. Furthermore, the focus is placed on how individual-level cognitive and behavioral factors, namely experience, intuition and overconfidence, affect the functioning of this heuristic.Design/methodology/approachFrom a theoretical standpoint, the authors build on dual-process theories and on the adaptive toolbox view from the “fast and frugal heuristics” perspective to develop an integrative conceptual framework that uncovers the mechanisms underlying the representativeness heuristic.FindingsThe authors’ conceptualization suggests that the search rule used in representativeness is based on analogical mapping from previous experience, the stopping rule is the representational stability of the analogs and the decision rule is the choice of the alternative upon which there is a convergence of representations and that exceeds the decision maker's aspiration level. In this framework, intuition may help the decision maker to cross-map potentially competing analogies, while overconfidence affects the search time and costs and alters both the stopping and the decision rule.Originality/valueThe authors develop a conceptual framework on representativeness, as one of the most common, though still poorly investigated, heuristics. The model offers a nuanced perspective that explores the cognitive and behavioral mechanisms that shape the use of representativeness in decision-making. The authors also discuss the theoretical implications of their model and outline future research avenues that may further contribute to enriching their understanding of decision-making processes.

Heuristic decision-making across adulthood.

“…The relative familiarity of two diseases or cities should not differ as a function of age given the obscurity of the unfamiliar option (Pachur et al, 2009). Finally, the representativeness heuristic draws on well-learned schemas and depends on the degree of similarity between the target person/event/sample and the population from which it is drawn (Galavotti et al, 2021). Schematic knowledge is preserved in healthy aging and is believed to be a major aid to memory when episodic details are forgotten (Siegel et al, 2020).…”

Heuristic Decision Making Across Adulthood

“…The relative familiarity of two diseases or cities should not differ as a function of age given the obscurity of the unfamiliar option (Pachur et al, 2009). Finally, the representativeness heuristic draws on well-learned schemas and depends on the degree of similarity between the target person/event/sample and the population from which it is drawn (Galavotti et al, 2021).…”

Role of Locus of Control in the Relationship between Behavioral Biases and Investment Decision

“…Consequently, different inclinations will result in diverse behaviors. It proves that psychological factors play a significant part in decision-making (Aksa & Wijayanti, 2022) Representativeness is reason in all above said phenomena and mostly leads investors to opt other suboptimal alternatives because of historical performance of companies (Kasoga, 2021;Galavotti et al, 2021). A negative relation between representative bias and investments is reported by Shah et al, (2018).…”