Abstract

The tax gap is a phenomenon experienced by revenue collection agencies which describes the difference between the taxes due, as prescribed by legislation, and the actual taxes collected. The tax gap is mostly a result of taxpayer non-compliance, such as the failure to submit a tax return. Recent theories suggest that a taxpayer’s social structure is a significant determinant of a taxpayer’s attitude towards tax compliance. This study explores the proposal that social network analysis through decision support systems can facilitate the objective of revenue collection agencies to minimize the tax gap. The results suggest that an agency’s limited enforcement capacity can achieve a greater impact on tax compliance by focusing on non-compliant social structures as opposed to single instances of non-compliance. The research fills a gap in literature by demonstrating IT’s value proposition towards government financial services.

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Social Network Analysis to Optimize Tax Enforcement Effort

The tax gap is a phenomenon experienced by revenue collection agencies which describes the difference between the taxes due, as prescribed by legislation, and the actual taxes collected. The tax gap is mostly a result of taxpayer non-compliance, such as the failure to submit a tax return. Recent theories suggest that a taxpayer’s social structure is a significant determinant of a taxpayer’s attitude towards tax compliance. This study explores the proposal that social network analysis through decision support systems can facilitate the objective of revenue collection agencies to minimize the tax gap. The results suggest that an agency’s limited enforcement capacity can achieve a greater impact on tax compliance by focusing on non-compliant social structures as opposed to single instances of non-compliance. The research fills a gap in literature by demonstrating IT’s value proposition towards government financial services.