This article aims to extend methodological possibilities for conducting research in accounting and auditing by providing an overview of how current developments in social network analysis (SNA) could serve as a powerful set of theoretical and methodological tools for this purpose. SNA focuses on structure and implication of network ties existing in particular empirical context. In contrast to classical quantitative methods (e.g. linear regression), SNA has the capacity to enable understanding of the emergence of the observed network by combining actors’ attributes and structures of relational ties existing between them. The paper notes the concept of interdependency, which is inherent element in any social relationship and which is of paramount importance in any social context. This paper introduces a number of important SNA concepts and provides references to software that researchers could utilize for different analyses. The example of a one-mode network between audit partners is presented, to which a number of previously outlined concepts are applied and discussed. Finally, we describe the potential of a cutting-edge statistical method for SNA, exponential random graph model (ERGM), which act as a cutting-edge pattern-recognition device for network structure.
|Journal||International Journal of Academic Research in Accounting, Finance and Management Sciences|
|Number of pages||16|
|Publication status||Published - 2017|