Evaluation of the Impact of Government Audit on Quality Management, Based on Neutroalgebra Generated by the PROSPECTOR Function

Abstract

The present study focuses on the evaluation of the impact of government audit on quality management, using a novel approach based on the neutralalgebra generated by the PROSPECTOR function. The central question of the research lies in the need to improve the effectiveness of government audits to ensure more efficient and transparent quality management in public institutions. The relevance of this issue is accentuated in the current context, where the pressure to optimize government processes is crucial to guarantee efficiency and public responsibility. Although there are various studies on government auditing, a significant gap has been identified in the literature regarding the use of methods that integrate indeterminacy and uncertainty, essential factors in quality assessment in complex environments. To address this gap, the study applies neutralalgebra through the PROSPECTOR function, allowing for more robust analysis of data obtained from audits. The results reveal that this approach is highly effective in capturing complexity and ambiguity in quality management, offering more detailed insight than traditional methods. The contributions of the study are diverse: first, it introduces an innovative method that refines the analysis of government auditing; Second, it provides practical recommendations that can be implemented to improve the quality in the management of public institutions. Ultimately, this work not only advances the theoretical understanding of government auditing in quality management, but also offers practical tools for its effective application in public administration.