Audit Resource Planning Success in B2b E-Commerce Engagement: An Empirical Assessment of Theorized Constructs, Manifest Variables Measurement and Second Order Factor Model
38 Pages Posted: 26 Apr 2006
Date Written: April 2006
Audit Resource planning (ARP) activity in any engagement involves a balancing act in between the significant outlays involved in the trained and skilled human resources and the audit objectives. Audit engagement for an e-commerce client makes ARP an activity full with technological complexities far removed from the traditional audit engagement with a conventional client and/or centralized accounting databases. These complexities of e-commerce technologies put a real pressure on audit organization's scarce human and financial resources. Despite these all, we have little understanding of how the success of such audit planning activity is measured. Present study makes use of classical measurement development frameworks used by the information systems researchers as well as the contemporary statistical methods for determining the dimensionality. This paper theoretically develops and empirically tests a measurement model of success of audit resource planning in e-commerce engagement. The model is restricted to the business-to-business (B2B) e-commerce category for simplicity. The results suggest that audit resource planning success (ARPS) can be operationalized as a second order factor model. The first order constructs of the model are termed higher technical training, higher technical experience, minimum breadth of technical training & experience, capabilities in professional audit judgment, and expertise in system and change management. These theorized constructs are found to be governed by the second order factor of ARP success. The results of the study are tools for benchmarking future ARP efforts by an audit organization and act as a base for operationalizing a key dependent variable in future ARP research.
Keywords: Audit Planning, Audit Resources Planning, Business-to-Business, E-Commerce Auditing, Confirmatory Factor Analysis, Structural Equation Modeling
JEL Classification: M10, M41, M49
Suggested Citation: Suggested Citation