Modeling antecedents and consequences of deliberative decision making within personnel selection

Date

2019-05-01

Journal Title

Journal ISSN

Volume Title

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Abstract

While hiring decisions are a frequent organizational occurrence that can substantially impact the decision maker, the organization, and/or society as a whole, employees do not always make optimal hiring decisions. This failure to make optimal decisions may occur because employees do not utilize deliberative processes (e.g., systematically gathering information, evaluating choice alternatives, taking time to decide etc.). Accordingly, the goal of the present study was to propose an integrative model of some antecedents and consequences of deliberative decision making within personnel selection. Data gathered from 322 hiring managers indicated that when managers felt accountable for their hiring decisions and possessed a deliberative decision making style, they were more likely to report making hiring decisions in a deliberative manner. This use of deliberation was, in turn, associated with high quality decisions (i.e., low regret, high satisfaction, and high performance ratings of the person that was hired). The results also indicated the relationship between accountability and decision quality was mediated by deliberative processes. These findings were consistent across multiple hiring decisions. Importantly, these results did not emerge when intuitive processes/style were examined. Collectively, these results help establish the ecological validity of various theories of decision making and specify that deliberative processes are associated with high quality selection decisions. These results can be leveraged by organizations who are interested in encouraging employees to utilize deliberative processes. Given the benefits of deliberative processes, these results may also be leveraged by workers who are interested in achieving higher task performance in their jobs.

Description

Keywords

Decision making, Deliberation, Personnel selection, Decision quality

Graduation Month

May

Degree

Master of Science

Department

Department of Psychological Sciences

Major Professor

Christopher J. Lake

Date

2019

Type

Thesis

Citation