Essays on decision sciences: exploring cognition, information processing, and complexity

This thesis provides three original contributions to the field of Decision Sciences. The first contribution explores the field of heuristics and biases. New variations of the Cognitive Reflection Test (CRT--a test to measure "the ability or disposition to resist reporting the response that first comes to mind"), are provided. The original CRT (S. Frederick [2005] Journal of Economic Perspectives, v. 19:4, pp.24-42) has items in which the response is immediate--and erroneous. It is shown that by merely varying the numerical parameters of the problems, large deviations in response are found. Not only the final results are affected by the proposed variations, but so is processing fluency. It seems that numbers' magnitudes serve as a cue to activate system-2 type reasoning. The second contribution explores Managerial Algorithmics Theory (M. Moldoveanu [2009] Strategic Management Journal, v. 30, pp. 737-763); an ambitious research program that states that managers display cognitive choices with a "preference towards solving problems of low computational complexity". An empirical test of this hypothesis is conducted, with results showing that this premise is not supported. A number of problems are designed with the intent of testing the predictions from managerial algorithmics against the predictions of cognitive psychology. The results demonstrate (once again) that framing effects profoundly affect choice, and (an original insight) that managers are unable to distinguish computational complexity problem classes. The third contribution explores a new approach to a computationally complex problem in marketing: the shelf space allocation problem (M-H Yang [2001] European Journal of Operational Research, v. 131, pp.107--118). A new representation for a genetic algorithm is developed, and computational experiments demonstrate its feasibility as a practical solution method. These studies lie at the interface of psychology and economics (with bounded rationality and the heuristics and biases programme), psychology, strategy, and computational complexity, and heuristics for computationally hard problems in management science.

Can a great resume hurt? Gender and contrast effects on recruiting

Recruiters make many inferences about applicants' abilities and interpersonal attributes on the basis of applicants' resumes. For example, every once in a while, a good resume leaves a strong positive impression and the recruiter creates a high expectation for the selection interview. What if a disappointing interview follows? Will the great resume help or hurt the candidate? The purpose of this study is to assess the impact of a good resume on the recruiter’s evaluation of a candidate when a non-enthusiastic interview follows as well as the interacting role of gender. The results of two online experiments (n=454) where participants played the role of the recruiter, showed that, on average, a very good resume (vs. no resume) before a non-enthusiastic interview did not affect the recruiter’s evaluation of the candidate. However, when the recruiter’s and the candidate’s gender were taken into consideration, a different picture emerged. While no effect was found for male recruiters, the candidate’s resume had a clear significant impact on female recruiter’s evaluations: when the candidate was also a female, the good resume shown before the non-enthusiastic interview performance tended to help, whereas when the candidate was a male, the good resume had a significant negative effect on female recruiters’ evaluation of the candidate. In sum, in situations where the resume had a strong impact on the recruiter’s evaluation (female recruiters), the direction of the effect was moderated by the candidate’s gender. Gender differences in information processing as well as in-group/out-group biases due to gender matching are used to hypothesize and explain the main findings.

Overconfidence and confirmation bias: are future managers vulnerable?

Decision makers often use ‘rules of thumb’, or heuristics, to help them handling decision situations (Kahneman and Tversky, 1979b). Those cognitive shortcuts are taken by the brain to cope with complexity and time limitation of decisions, by reducing the burden of information processing (Hodgkinson et al, 1999; Newell and Simon, 1972). Although crucial for decision-making, heuristics come at the cost of occasionally sending us off course, that is, make us fall into judgment traps (Tversky and Kahneman, 1974). Over fifty years of psychological research has shown that heuristics can lead to systematic errors, or biases, in decision-making. This study focuses on two particularly impactful biases to decision-making – the overconfidence and confirmation biases. A specific group – top management school students and recent graduates - were subject to classic experiments to measure their level of susceptibility to those biases. This population is bound to take decision positions at companies, and eventually make decisions that will impact not only their companies but society at large. The results show that this population is strongly biased by overconfidence, but less so to the confirmation bias. No significant relationship between the level of susceptibility to the overconfidence and to the confirmation bias was found.