Date of Award

Spring 2008

Document Type

Dissertation

Degree Name

Doctor of Business Administration (DBA)

Department

Management

First Advisor

Marcia Dickerson

Abstract

In the 15 years since Bateman and Crant (1993) formulated the construct of proactive personality, numerous researchers have devoted a significant amount of attention to proactive attributes and behaviors (e.g., Parker, Williams, & Turner, 2006; Crant, 2000; Frese & Fay, 2001; Parker, 2000; Erdogan & Bauer, 2005). Campbell's (1990) model of performance suggests that an organization's selection system may ultimately promote proactive behavior. Consequently, in this dissertation, I advocate a selection approach as the initial building block towards creating a workplace in which proactive behavior is a fundamental outcome.

One of the selection tools yet to be explored by researchers and practitioners as a method of hiring proactive employees is biographical data. Biographical data, or biodata, is collected by asking a person to describe or report prior behaviors and experiences (Nickels, 1994) based on the rationale that an individual's past behavior provides some indication of what behavior is likely in the future (Childs & Klimoski, 1986; Nickels, 1994; Owens & Schoenfeldt, 1979; Mumford & Owens, 1987). Therefore, a proactivity-related biodata measure (PROBIO) was developed to predict proactive behavior based on the rationale that an individual who has been proactive in the past is likely to be proactive in the future.

In addition to developing a biodata measure to predict proactive behavior, one of the objectives of this dissertation was to provide a better understanding of the relationship between proactive behavior and job performance. Campbell's (1990) model of performance suggests that supervisors will differ in their evaluations of proactive behavior based upon the utility they attach to such behavior. Therefore, in addition to examining the relationship between proactive behavior and job performance, supervisor learning goal orientation was examined as a potential moderator of that relationship.

Findings indicated that proactivity-related biodata is useful in predicting general proactive behavior. It was important to compare the predictive validity of the newly constructed PROBIO measure to that of proactive personality, a commonly studied predictor of proactive behavior (e.g., Detert & Burris, 2007). Therefore, the first meta-analytic review of proactive personality was conducted. Interestingly, when predicting proactive behavior, several of the PROBIO factors in this study offered a predictive validity similar to that demonstrated by proactive personality in the meta-analysis. Further, the results suggested that, in some cases, proactivity-related biodata provides incremental predictive validity for proactive behavior above that obtained by proactive personality.

In addition to providing a benchmark of predictive validity, results of the proactive personality meta-analysis have several implications for research in the area. Findings indicated that the predictive validity of proactive personality may differ based upon the type of proactive behavior chosen as the criterion of interest (e.g., voice versus taking charge). Results also suggested that the correlation between proactive personality and proactive behavior was significantly higher when the behavior was self-reported rather than provided by another source.

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