More attention is being given to the stable, dispositional tendency to maximize when making decisions. Within the growing body of research has been an exchange regarding the appropriate means of measuring maximizing tendency. Guided primarily by psychometric and statistical analyses, these studies have critiqued and revised existing maximizing tendency scales and/or introduced new measures. Importantly, many of these discussions seem to ignore theoretical considerations of the construct of maximizing. In this article, we revisit the original work of Herbert Simon, from where the theory of maximizing tendency was developed, and provide a theoretical account for how maximizers can be distinguished from satisficers and the implications therein for the measurement of maximizing tendency. Across two studies, we provide an updated psychometric, correlational, and behavioral comparison of the two most popular maximizing tendency scales: the Maximization Scale and the Maximizing Tendency Scale. Results demonstrate that the Maximizing Tendency Scale is more theoretically and psychometrically valid than the Maximization Scale. Copyright © 2015 John Wiley & Sons, Ltd.Additional supporting information may be found in the online version of this article at the publisher's web-site.key words maximizing tendency; maximize; satisfice; theoretical evaluation; psychometric evaluationOver the past decade, increased attention has been given to the dispositional tendency to maximize; within this growing body of research is a debate regarding the proper measurement of maximizing tendency. What has been given less attention, however, is the theory of maximizing and how it relates to the measurement of maximizing tendency. Indeed, many of the articles have attempted to identify the best measure of maximizing tendency based primarily on psychometric evidence ignoring the theory of the construct. This is problematic insofar as appropriate measurement of psychological variables hinges upon sound theories of constructs. The primary purpose of this article, therefore, is to present a theoretical justification for the measurement of maximizing tendency. The secondary purpose is to provide a comparison of the two most popular maximizing tendency scales: the Maximization Scale (MS; Schwartz et al., 2002) and the Maximizing Tendency Scale (MTS; Diab, Gillespie, & Highhouse, 2008). Across two studies, we examine which scale performs better psychometrically and theoretically. The theory of maximizing tendencyThe concept of maximizing was derived from Simon's (1955Simon's ( , 1956) work on satisficing. Simon argued that the normative, rational model of decision making-wherein decision-makers consider all alternatives, choosing the utility-maximizing option-was incompatible with the limits of basic human information and computational processing.Stated differently, humans could not optimize their decisions as would be suggested by the rational-man model of decision making. Instead, Simon argued, individuals elected to find an alternative that ...

As teams continue to become more prevalent in modern-day organizations, researchers and organizations alike can benefit from a more nuanced understanding of teams’ decision-making process, which can ultimately impact organizational effectiveness. Although team processes are conceptualized as dynamic phenomena, they have largely been treated as static in research. In this study, we draw on the input-mediator-output-input and episodic team performance frameworks to advance a theoretical model of the dynamic, reciprocal effects of team rational decision strategy and team performance as well as the role of team composition of individual rational decision style. We sampled 320 participants in 85 teams competing in a 10-week business strategy simulation where teams made weekly strategic decisions that contributed to team performance. Teams composed of individuals with rational decision styles were more likely to adopt rational decision strategies, which led to better team performance. Additionally, results revealed a positive reciprocal effect between rational decision strategy and team performance such that teams with positive prior performance were more likely to engage in subsequent rational decision strategy. As hypothesized, team composition of members’ rational decision style was the primary determinant of team rational strategy during initial stages of team development, but the valence of outcome feedback (i.e., prior performance) took over as the stronger predictor of team rational strategy during later stages of team development. We contribute to the team and decision-making literatures by examining the dynamic process of team decision making and team performance.

In an effort to bridge the scientist–practitioner gap in the employee selection, some researchers have advocated telling stories to better communicate the value of evidence‐based hiring practices to human resource (HR) professionals. In this paper, we conducted two experiments that examine the efficacy of storytelling for overcoming managers’ resistance to use structured job interviews. In two experiments, we found that participants who read a story regarding the effectiveness of structured interviews, as opposed to receiving evidence‐based advice, reported more favorable attitudes toward structured job interviews. Serial mediation analysis revealed that the observed attitude change was mediated by an increase in narrative transportation and reduction in counterarguing. Implications for using stories in communicating the value of evidence‐based HR practices are discussed.

Landers and Behrend (2015) call for editors and reviewers to resist using heuristics when evaluating samples in research as well as for researchers to cautiously consider choosing the samples appropriate for their research questions. Whereas we fully agree with the former conclusion, we believe the latter can be extended even further to encourage researchers to embrace the strengths of their samples for understanding their research rather than simply defending their samples. We believe that samples are not inherently better or worse but rather better suited for different research objectives. In this commentary, we identify three continua on which research goals can differ to demonstrate that all samples can inform science. Depending on the position of one's research on these continua, different samples exhibit different strengths; the continua described below can be used to anchor one's sample to demonstrate how it can benefit, rather than limit, research conclusions. As discussed in the focal article, researchers will often apologize for their convenience samples as one of a litany of limitations; we hope that researchers will move sampling issues out of the limitations section and into the main discussion.

Abstract. Maximizing Tendency is a decision style characterized by holding a higher standard for one’s decision. Initially, this style had been linked to negative life outcomes (e.g., decision regret, life dissatisfaction, depression), but recent studies have begun to show the opposite. In this study, we argue and test the proposition that relations between maximizing and future-oriented outcomes can be explained by future-oriented thinking. Results show that maximizers are more likely to consider the future consequences of their current actions. In turn, maximizers intend to save more, have more savings, show a greater concern for guiding the next generation, and are less likely to engage in temporal discounting behaviors. The study concludes that maximizing can be a beneficial decision style due, in part, to its impact on future-oriented thinking, and adds to a growing literature suggesting that maximizing can, in fact, be a good thing.