IPSAS and the Big Four: further evidence incorporating political and social power theory – a cross-country study
Mustafa Elkasih Abdulkarim & Mohamed Ismail Umlai
Abstract
Purpose This study aims to examine the influence of economic power, as exemplified by the Big-4 accounting firms, and identity power on the adoption of International Public Sector Accounting Standards (IPSAS). Design/methodology/approach This study draws on the models developed by Fuchs (2007) and Simon and Oakes (2006) to operationalize variables representing economic power and identity power. The study uses ordinary least squares, probit and logit regressions, as well as fixed-effects specifications using a sample of 79 countries. Findings The economic power of the Big-4 is strongly associated with the level of IPSAS adoption, whereas societies with lower social cohesion and weaker identity power are less likely to implement IPSAS. Thus, IPSAS adoption depends not only on economic power but also on a country’s social context. Research limitations/implications Policymakers and both global and local standard setters should monitor the influence of the Big-4 to prevent disproportionate dominance and promote equitable reform. Additionally, policymakers should actively communicate the benefits of public-sector accounting reform, particularly in societies with lower cohesion. Reform strategies should emphasize spreading IPSAS adoption as an integral component of broader accounting reforms. Social implications Looking at Big-4 concentration or market/economic power is likely to be a good avenue, with their influence on policy and accounting development across countries. Originality/value To the best of the authors’ knowledge, this study is novel in empirically examining IPSAS adoption through the lens of political and social psychology power theories across multiple countries.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.