Common method variance (CMV) bias: its implications, how to detect it, and how to handle it

Common method variance (CMV) bias is commonly encountered in cross-sectional survey data in HRM generally, and HRD studies specifically. Despite a substantial and polarized debate over the issue and the proposal of various methods for detecting and handling it, confusion persists. This paper starts by clearly defining the problem and explaining the conditions under which it occurs. We explore the impact of CMV both when it affects the dependent and independent variables, and when it pertains only to independent variables. We then discuss commonly proposed solutions, paying specific attention to their limitations. We end with some general recommendations on detecting and dealing with CMV bias.