Paper Number

ICIS2025-1787

Paper Type

Short

Abstract

While advances in artificial intelligence offer new opportunities, the digital transformation of public administration continues to face persistent underlying challenges. One key barrier is public employees' lack of data literacy, limiting their ability to support digital and AI-driven change. This study applies the institutional logics perspective to examine how adherence to a legalistic-bureaucratic or managerial logic influences data literacy self-efficacy in local governments. Based on a survey among 82 employees of German local governments, we estimate three regression models across the data literacy dimensions of data identification, data processing, and data management and sharing. Results show that managerial logic is positively associated with data identification, while legalistic-bureaucratic logic is positively associated with data management and sharing. These findings suggest that institutional logics shape public employees’ perceived data capabilities and willingness to engage with data.

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Dec 14th, 12:00 AM

The Influence of Institutional Logics on Data Literacy Self-Efficacy in Local Governments

While advances in artificial intelligence offer new opportunities, the digital transformation of public administration continues to face persistent underlying challenges. One key barrier is public employees' lack of data literacy, limiting their ability to support digital and AI-driven change. This study applies the institutional logics perspective to examine how adherence to a legalistic-bureaucratic or managerial logic influences data literacy self-efficacy in local governments. Based on a survey among 82 employees of German local governments, we estimate three regression models across the data literacy dimensions of data identification, data processing, and data management and sharing. Results show that managerial logic is positively associated with data identification, while legalistic-bureaucratic logic is positively associated with data management and sharing. These findings suggest that institutional logics shape public employees’ perceived data capabilities and willingness to engage with data.

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