A conceptual model of the influence of résumé components on personnel decisions: a policy-capturing study on résumé screening
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Date
2020
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Abstract
Based on a literature review of not only industrial and organizational psychology but also decision theory, we have developed a conceptual model of résumé screening. It postulates that personnel decisions concerning assignment to particular categories result from a gradual process with an underlying initial assumption, and the decision-making process varies depending on specific conditions. Under different conditions, decision makers utilize different résumé components (relevant, irrelevant and formal), whose impacts might interact with each other. We designed and conducted two policy-capturing experimental studies and employed a machine learning approach and a decision tree classification method to verify our conceptual model. The results indicate that it might be considered valid and might explain actual decisions regarding résumés. The data we have collected suggests that in a situation of certainty recruitment specialists make their decisions solely on the basis of information obtained from relevant résumé components and apply straightforward, i.e., non-compensatory, rules. However, when making decisions in a situation of uncertainty, recruitment specialists make an attribution and are influenced by the combined interactive effect of relevant, non-relevant and formal components of résumés. These decisions, in turn, are compensatory in nature. For example, positive personnel decisions regarding the appraisal of a résumé may be made if deficiencies in a relevant area are compensated for by an exceptional level of non-relevant or formal components.
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resume screening, decision-making, personnel decisions, policy-capturing study
Citation
Grobelny, J., Frontczak, P., Pawlak, K., Skorodzillo, U., Szymanowska, M., & Wilczynska, S. (2020). A conceptual model of the influence of résumé components on personnel decisions: a policy-capturing study on résumé screening. Journal of Management Information and Decision Sciences, 23(2), 57-78.
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1524-7252