To read this content please select one of the options below:

Shedding Light on Invisible Influences: Reviewing HROB Scholars' Use of Unmeasured Latent Method Factors

Christopher M. Castille (Nicholls State University, USA)
Larry J. Williams (Texas Tech University, USA)

Research in Personnel and Human Resources Management

ISBN: 978-1-83797-890-8, eISBN: 978-1-83797-889-2

Publication date: 26 September 2024

Abstract

In this chapter, the authors critically examine the application of unmeasured latent method factors (ULMFs) in human resource and organizational behavior (HROB) research, focusing on addressing common method variance (CMV). The authors explore the development and usage of ULMF to mitigate CMV and highlight key debates concerning measurement error in the HROB literature. The authors also discuss the implications of biased effect sizes and how such bias can lead HR professionals to oversell interventions. The authors provide evidence supporting the effectiveness of ULMF when a specific assumption is held: a single latent method factor contributes to the data. However, the authors dispute this assumption, noting that CMV is likely multidimensional; that is, it is complex and difficult to fix with statistical methods alone. Importantly, the authors highlight the significance of maintaining a multidimensional view of CMV, challenging the simplification of a CMV as a single source. The authors close by offering recommendations for using ULMFs in practice as well as more research into more complex forms of CMV.

Keywords

Citation

Castille, C.M. and Williams, L.J. (2024), "Shedding Light on Invisible Influences: Reviewing HROB Scholars' Use of Unmeasured Latent Method Factors", Buckley, M.R., Wheeler, A.R., Baur, J.E. and Halbesleben, J.R.B. (Ed.) Research in Personnel and Human Resources Management (Research in Personnel and Human Resources Management, Vol. 42), Emerald Publishing Limited, Leeds, pp. 215-250. https://doi.org/10.1108/S0742-730120240000042007

Publisher

:

Emerald Publishing Limited

Copyright © 2024 Christopher M. Castille and Larry J. Williams