Abstract
Traditionally, studies examining decision-making heuristics and biases (H&B) have focused on aggregate effects using between-subjects designs in order to demonstrate violations of rationality. Although H&B are often studied in isolation from others, emerging research has suggested that stable and reliable individual differences in rational thought exist, and similarity in performance across tasks are related, which may suggest an underlying phenotypic structure of decision-making skills. Though numerous theoretical and empirical classifications have been offered, results have been mixed. The current study aimed to clarify this research question. Participants (N = 289) completed a battery of 17 H&B tasks, assessed with a within-subjects design, that we selected based on a review of prior empirical and theoretical taxonomies. Exploratory and confirmatory analyses yielded a solution that suggested that these biases conform to a model composed of three dimensions: Mindware gaps, Valuation biases (i.e., Positive Illusions and Negativity effect), and Anchoring and Adjustment. We discuss these findings in relation to proposed taxonomies and existing studies on individual differences in decision-making.
Section snippets
Literature review
Before introducing the dimensions found, we shortly describe different approaches present in the literature for grouping H&B. We start with some classic studies on individual differences and biases since they allowed detecting the first decision-making categories present in literature (e.g., “Positive Illusions”, “Negativity effect”, “Mindware gaps”). Cognitive models (e.g., “Dual process theory”) used to support empirical classifications are briefly introduced in the second section of the
Scope and strategy of analysis
Considering the various empirical and theoretical classifications and respective methodological weaknesses, the current study, with the aim of overcoming such limits, introduced a three-step analysis procedure in order to develop more inclusive H&B dimensions. We started from theoretical bias classifications. Since the current literature presents >100 types of biases, often studied in isolation, taxonomies were certainly a good starting point for sampling H&B categories. Therefore, a Multiple
Multiple Correspondence Analysis (MCA)
In order to perform a MCA, existing taxonomies and classifications with more than two dimensions were used to select H&B on the most comprehensive dimensions (i.e., Arnott, 2006; Baron, 2000; Carter et al., 2007; Gilovich et al., 2002; Oreg & Bayazit, 2009; Stanovich et al., 2008). Multiple Correspondence Analysis is an exploratory descriptive method; the multivariate extension of the Correspondence Analysis for analyzing tables containing three or more variables. It can be considered as a
General discussion
This research aimed to empirically identify underlying relationships between different H&B for clustering them. Such findings are in line with several theorizations on the H&B taxonomies (Arnott, 2006; Baron, 2000; Carter et al., 2007; Gilovich et al., 2002; Oreg & Bayazit, 2009; Stanovich et al., 2008) and cognitive models which suggest the presence of more than two dimensions of biases (see Stanovich, 2009). Our dimensional account is strictly connected to the H&B tasks selected to compose
Future directions and limitations
Although these results are promising, we must acknowledge several limitations that could represent the focus of future research. First, to reduce participant burden, our individual indicators for each H&B were limited to a small set, or a single-item. This limits our ability to address the internal consistency of the underlying tasks used in this study. However, it is important to note that repeated-measures of H&B often show acceptable internal consistency when multiple items are used to
Conclusion and practical implications
The utility of this study and its contribution on individual-difference decision-making paradigm in the academic research is related to the possibility of developing a wider and more comprehensive taxonomy of H&B, still grounded on an evidence-based approach. Adopting evidence-based categories of H&B may allow future research to investigate more precisely the presence of multiple processes in decision-making against the idea of a single Decision-Making Competence (see Ceschi, Costantini,
Andrea Ceschi is a post-doc Work and Organizational Psychology at Verona University (Italy), Department of Human Sciences. His field of work deals with organisational dynamics related to decision-making processes in the workplace.
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Andrea Ceschi is a post-doc Work and Organizational Psychology at Verona University (Italy), Department of Human Sciences. His field of work deals with organisational dynamics related to decision-making processes in the workplace.
Arianna Costantini is a Ph.D. Candidate in Psychology at Verona University, Department of Human Sciences, Italy. Her field of work is job crafting, behavior change and workplace innovation.
Riccardo Sartori is Associate Professor in Work and Organizational Psychology at Verona University (Italy), Department of Human Sciences. His field of work is organizational innovation and the assessment processes linked to this topic, included psychological assessment and human resources management.
Joshua Weller is an Assistant Professor of Developmental Psychology at Tilburg University, The Netherlands. His research focuses broadly on individual differences in decision making and risk taking.
Annamaria Di Fabio is full professor of Work and Organizational Psychology and director of the two International Laboratories for Research and Intervention Cross-Cultural Positive Psychology, Prevention, and Sustainability (CroCPosPsychP&S) and Psychology for Vocational Guidance, Career Counseling and Talents (LabOProCCareer&T) at the University of Florence. Recently she was elected in the Board of Directors of the International Association of Applied Psychology (IAAP).
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