A research agenda for muti-attribute utility analysis in human resource management

Abstract Most applications of utility analysis in Human Resource Management have focussed upon only one outcome of a selection system-the value of job performance in dollars. Multi-attribute utility (MAU) analysis allows decision makers to incorporate multiple outcomes into their analytic decisions. MAU also increases the participation of decision makers in the utility analysis process by asking them what factors to consider, how to measure the factors, and what functions should be used to combine them. This manuscript outlines the steps necessary to conduct MAU analysis and delineates research issues that arise from using a MAU approach. Based on these issues, we suggest systematic research questions and directional hypotheses which will improve our understanding and implementation of MAU procedures in organizations. The topics, derived from utility analytic and groups research literatures, include contrasting single attribute utility analysis with MAU, examining the effect of MAU on decision maker attitudes, the ability of MAU to explicate managerial policies, and improving existing MAU approaches using results from the group research literature.

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