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Digging deeper or piling it higher? Implicit measurement in organizational behavior and human resource management
Organizational researchers can dig deeper into peoples' thoughts, attitudes, and self-concepts to understand how automatic processes may impact judgment and social behavior in organizations. Measures of these automatic processes, including the Implicit Association Test (e.g., IAT; Greenwald, Mc...
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Published in: | Human resource management review 2013-09, Vol.23 (3), p.229-241 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Organizational researchers can dig deeper into peoples' thoughts, attitudes, and self-concepts to understand how automatic processes may impact judgment and social behavior in organizations. Measures of these automatic processes, including the Implicit Association Test (e.g., IAT; Greenwald, McGhee, & Schwartz, 1998), Semantic Priming (e.g., SP; Wittenbrink, Judd, & Park, 1997), Affect Misattribution Procedure (e.g., AMP; Payne, Cheng, Govorun, & Stewart, 2005), Word Completion Tasks (e.g., WCT; Johnson & Saboe, 2011), among many others, deserve greater attention as alternatives or supplements to traditional self-report measures of variables important in organizations (e.g., job satisfaction, personality and trait measurement, diversity attitudes). In this paper, we first provide a primer on implicit social cognition and its relationship to automatic and controlled cognitive processes, discussing major types of implicit measures, how these might operate, criticisms of this approach, and how these implicit constructs may give rise to behavior in organizations. Second, we discuss models of automatic processes and explore their validity and how these may predict behavior. Third, we offer advice for selecting, constructing, and improving implicit measurements when used in organizational research to enhance human resources and organizational functioning. |
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ISSN: | 1053-4822 1873-7889 |
DOI: | 10.1016/j.hrmr.2012.12.004 |