An Examination of Biodata Theory‐Based Constructs in a Field Context

Abstract

This study examined whether items from a biodata inventory were consistent with theorybased constructs as suggested by the ecology model. The model posits five constructs explain biodata predictive ability. Items were sorted using the theory-based construct domains. The resulting scale scores were assessed for evidence of content, criterionrelated, and construct validity in a sample of 6032 automated systems controllers. Results suggested moderate support for the theory-based constructs. A notable finding was that items capturing a theoretical construct were impacted by the life stage in which they were anchored. Results further suggest the need to examine if certain life stages are more predictive than others or perhaps if certain constructs are more predictive when related to a particular life stage.

Developing Biodata for Public Manager Selection Purposes: A Comparison between Fuzzy Logic and Traditional Methods

“…The quasi-rational approach has the advantages derived from both previous approaches, given that it has demonstrated its relationship with criteria, as in the empirical approach, and is easier to explain and defend among non-experts (Mael & Hirsch, 1993). Regardless of the method chosen, it is advisable to compute relationships between biodata and criteria (Cucina et al2013), given that Mitchell and Klimoski (1982) have referred to the loss of predictability of biodata over time, due to time moment and context effects (Dean & Russell, 2005), and in response to changes in job skills requirements, criterion measurement, and organizational policies for personnel selection.…”

“Embedded” at hire? Predicting the voluntary and involuntary turnover of new employees

“…Biodata has been linked to outcomes ranging from performance to relationship quality (Mount, Witt, & Barrick, 2000), as well as to voluntary turnover (Barrick & Zimmerman, 2005). Despite this demonstration of success, however, scholars have criticized biodata research for taking an actuarial approach, noting a lack of sound theory to explain these effects (Breaugh & Dossett, 1989;Dean & Russell, 2005).…”

Applying theory to the black box: A model for empirically scoring biodata

“…To develop the empirical keys, point‐biserial correlations were computed between dichotomized response options (i.e., chose response = 1, did not choose response = 0) and job performance to create response weights . These correlations became the points awarded for choosing that response option, and points were then summed across all item responses to determine scores on the biodata inventory (for more detail on this method, see Cucina et al, ; Dean & Russell, ; Devlin et al, ). Cucina and colleagues endorse this option‐level correlation keying procedure, given its ease of use in statistical packages and similar performance to other empirical‐keying techniques.…”