When the world isn\u27t always flat: The impact of psychological distance on auditors\u27 reliance on specialists

This study addresses recent calls for research on the conditions influencing auditor decisions related to PCAOB-encouraged reliance on third-party experts. To this end, the present study explores the effect of psychological distance on external auditors\u27 reliance when induced through physical distance in a telework relationship between an auditee and a specialist. The reliance decision focuses on the auditee\u27s contracting with a computer audit specialist who works remotely through a telework arrangement. The psychological distance associated with this telework arrangement is examined both in the context of variance in the physical distance of the computer audit specialist and the interactive effect of a contextual factor-the historical experience with an auditee\u27s internal audit function. A 2 x 2 experiment with a total of 121 experienced Big 4 auditors is conducted in which psychological distance (physically proximate or remote specialist) and historical experience with an auditee\u27s internal audit function (presence or absence of a prior year material weakness in internal controls) are manipulated. Consistent with predictions based on construal level theory, we find that psychological distance affects auditors\u27 reliance judgment such that increased distance leads to lower reliance. Furthermore, the historical experience with the auditee\u27s internal audit function creates a halo effect which moderates the effect of psychological distance such that the differential effect of a present vs. absent prior year material weakness on auditors\u27 confidence and associated willingness to reduce budgeted audit hours is larger for a psychologically distant specialist. The results of this study suggest that an auditee\u27s choice of a more proximate specialist may garner greater reliance by the external auditor, particularly when there is a material weakness in the prior year audit that the specialist is intended to help ameliorate. (C) 2014 Elsevier Inc All rights reserved