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E-Files are a cornerstone of modern public administrations but acceptance of its use by all employees remains a challenge. While surveys can be used to gauge employees acceptance and attitudes towards E-Files, self-selection biases might skew the results and thus lead to suboptimal decisions. In the present paper, a survey was conducted asking German public administration employees (n = 169) about their perceived advantages and disadvantages of E-Files. To detect potential biases, affinity for technology interaction as well cognitive and affective attitudes towards E-Files were assessed. Results show a strong selection bias that is not immediately apparent from the sociodemographic variables. Despite this bias, valuable insights can be gained regarding the improvement of E-Files, especially when taking advantages of paper files into account. By assessing potential self-selection biases and motivating reluctant employees, biases can be avoided and better conclusions can be drawn to improve e-government digitalization projects.

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E-Files in Public Administration - Biases and Uses

  • 会议论文

  • 发表日期：

    2026年

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  • Daniel Wessel,
  • Florian König,
  • Moreen Heine

摘要

E-Files are a cornerstone of modern public administrations but acceptance of its use by all employees remains a challenge. While surveys can be used to gauge employees acceptance and attitudes towards E-Files, self-selection biases might skew the results and thus lead to suboptimal decisions. In the present paper, a survey was conducted asking German public administration employees (n = 169) about their perceived advantages and disadvantages of E-Files. To detect potential biases, affinity for technology interaction as well cognitive and affective attitudes towards E-Files were assessed. Results show a strong selection bias that is not immediately apparent from the sociodemographic variables. Despite this bias, valuable insights can be gained regarding the improvement of E-Files, especially when taking advantages of paper files into account. By assessing potential self-selection biases and motivating reluctant employees, biases can be avoided and better conclusions can be drawn to improve e-government digitalization projects.