کاوش عمیق تر و یا ستون بندی بیشتر آن؟ اندازه گیری ضمنی در رفتار سازمانی و مدیریت منابع انسانی

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.

Because organizations are social systems, processes in thinking, perceiving others, and understanding behavior are important in understanding organizational processes and effectiveness (Katz & Kahn, 1978). Many people take comfort that their conscious thoughts, declarative knowledge, and deliberate intentions guide their decision-making processes and social behavior. Advances in implicit measurement, however, indicate that some thought processes may be less accessible than one may assume (Greenwald and Banaji, 1995 and Nisbett and Wilson, 1977), and may operate automatically (e.g., Bargh, 1994). The space between conscious reflection and accurate assessment has motivated researchers to develop measures of these automatic processes for digging deeper into people's thoughts, goals, and self-knowledge (e.g., Fazio et al., 1995, Greenwald et al., 1998 and Payne et al., 2005). However, with these advances, the question remains how do we impact and improve organizations as we dig deeper into measuring these automatic processes that govern cognition, attitudes, and behaviors? Or does this line of research simply pile higher our knowledge of biases, limitations, and criticisms preventing us from further improving organizational behavior and effectiveness? Implicit measurement poses both opportunities and challenges for organizational researchers. In terms of opportunities, digging deeper using implicit measures, such as the Implicit Association Test (IAT; Greenwald et al., 1998), Semantic Priming tasks (SP; e.g., Wittenbrink, Judd, & Park, 1997), the Affect Misattribution Procedure (AMP; Payne et al., 2005), Name Letter Effects procedure (NLE; Nuttin, 1985), and Word Completion Tasks (WCT; e.g., Johnson and Saboe, 2011 and Johnson et al., 2010), among others, may provide additional approaches for assessing thoughts and feelings when social desirability, lack of introspective access, and faking may distort declared or stated beliefs (Podsakoff et al., 2003 and Podsakoff and Organ, 1986). Using these measures offers an alternative to understanding and improving organizations because we can now measure a person's attitudes, stereotypes, and prejudices from two perspectives, one explicit, and one implicit, and link these separately, jointly, and incrementally to each other and organizational phenomena to enhance theory and improve organizations. In terms of challenges, the routine inclusion of implicit measures in research has not been without criticism, debate, and caution (e.g., Arkes and Tetlock, 2004, Blanton and Jaccard, 2006, Blanton et al., 2009, DeHouwer et al., 2009, Fazio, 2007, Fazio and Olson, 2003, Gawronski et al., 2007, Karpinski and Hilton, 2001, Landy, 2008, McConnell and Leibold, 2009 and Ziegert and Hanges, 2009). Many of these arguments (e.g., use of real world criteria) regarding implicit measurement often also apply to the use of explicit or traditional forms of measurement. Further, there remains considerable debate regarding the meaning and usefulness of measures of automatic cognitive processes and the extent to which they provide distinct information about inner thoughts and states that truly relate to important, measureable behaviors in organizations or society at large. Instead of piling higher cautions and admonitions about the use of these measures in organizations, we look at these problems as challenges and as opportunities for future research to fully evaluate the efficacy of such measures to assist us in improving workplaces and organizations. The purpose of this paper is to review the social cognitive perspective on the measurement of automatic cognitive processes and how these relate to organizational outcomes. We review the theoretical basis and the validity evidence for these measures, and suggest several research strategies for those interested in using, critiquing, and improving implicit measurement in organizational research. We discuss many judgment processes in organizations and how these may be impacted by implicit cognition as we take a deeper, process-oriented, and more critical view of implicit cognition in organizations (Haines and Sumner, 2006, Johnson and Steinman, 2009 and Sumner and Haines, 2004). Finally we briefly provide practical advice to organizational researchers interested in exploring implicit measurement and automatic processes to both understand and improve organizational behavior.

Implicit measures offer an additional method for assessing organizational constructs and potentially shedding light on slippery constructs such as work self-concept or attitude change in response to training. While there has been considerable discussion of the meaning and application of implicit measures (Landy, 2008), including the conditions where they will predict behavior, and their usefulness above and beyond explicit measures, the theoretical and conceptual advantages are still being debated. At the same time, some of the concerns regarding the utility of implicit measurement should not focus solely on a simple association model where an implicit measure of an organization outcome such as turnover, job satisfaction, or worker evaluation. Instead, we believe that the best way to address the “implicit measure issue” is to routinely ask finer-tuned questions. Among these are: Is it possible that automatic processes affect constructs that are of interest to my organization? When norms are strong to report a particular response (e.g., I learned a lot during training, I view social groups equally, I love my job), is it possible that an implicit measure may be a helpful complement to an explicit measure? Are the known moderators of the relationship between automatic process and behavior, such as motivation or cognitive load, routinely present in my organization? Should I be mindful of just the added effects that an implicit measure may “buy me,” or can I also explore the possible multiplicative effects that occur when implicit and explicit thoughts are at odds with one another? These questions might motivate organizational researchers to look beyond the known validity and reliability of implicit measures, and to begin investigations of these second generation questions (Nosek et al., 2001). In sum, by digging deeper into thoughts, attitudes, and cognitive processes of individuals, we may pile higher our understanding of the behavior of people in organizations, and perhaps the behavior of organizations themselves.