Unlocking the Potential of Other-ratings for Human Resource Management Research

Abstract

Self-report questionnaires are the predominant method used in human resource management (HRM) research to assess employees’ work-related psychological constructs (e.g., processes, states, and attributes). However, this method is associated with significant shortcomings, including the introduction of self-serving bias and common method variance when used exclusively. In this chapter, the authors challenge the assumption that individuals themselves are the only accurate source of the self-focused information collected in HRM research. Instead, the authors propose that other-ratings – ratings of a target individual that are provided by a workplace observer, such as a coworker, supervisor, or subordinate – can accurately assess commonly measured work-related psychological constructs. The authors begin by explaining the advantages of other-ratings for HRM research and practice, reviewing the history of other-ratings and how they emerged in the personality and person-perception literature, and outlining how they have been used in HRM research to date. Then, the authors build upon Funder’s (1995) realistic accuracy model to develop a theoretical argument detailing why workplace others should be able to accurately judge how another employee thinks and feels about work. Next, the authors highlight existing evidence in the literature on the accuracy of other-ratings and present the results of a preliminary meta-analysis on the ability of other-ratings to predict self-ratings of work-related psychological constructs. Finally, the authors discuss potential moderators of other-rating accuracy and reflect on a number of practical considerations for researchers looking to use other-ratings in their own work. The authors intend for this chapter to meaningfully contribute to the larger conversation on HRM research methods. Other-ratings are a simple, yet powerful, addition to the methodological toolkit of HRM researchers that can increase flexibility in research design and improve the overall quality of research.