Ötting, Sonja Kristine: Artificial intelligence as colleague and supervisor: Successful and fair interactions between intelligent technologies and employees at work. 2021
Content
- Summary
- Table of contents
- Introduction
- Theoretical Background
- Aims and Outline of the Present Work
- Study 1 – Let's Work Together: A Meta-Analysis on Robot Design Features that Enable Successful Human–Robot Interaction at Work
- Study 2 – The Importance of Procedural Justice in Human–Machine Interactions: Intelligent Systems as New Decision Agents in Organizations
- Study 3 – How Procedural Justice Works: Artificial Intelligence as New Decision Agent and the Mediation of Justice Effects
- General Discussion
- Theoretical Implications
- Practical Implications
- Strengths and Limitations
- Directions for Future Research
- Conclusion
- References
- Statement of Authorship
- Dissertation Sonja Ötting_overview
- Dissertation Sonja Ötting_Druck_vor der Prüfung
- Manuscript of Study 3
- How Procedural Justice Works in Organizations
- How Procedural Justice Works for AI Decisions
- The Present Studies
- Study 1
- Method
- Results
- Preliminary Analyses
- Descriptive Statistics
- Mediation of Procedural Justice Effects
- Moderated Mediation of Procedural Justice Effects
- Discussion
- Study 2
- Method
- Results
- Preliminary Analyses
- Descriptive Statistics
- Mediation of Procedural Justice Effects
- Moderated Mediation of Procedural Justice Effects
- Discussion
- General Discussion
- Theoretical Implications
- Practical Implications
- Limitations and Directions for Further Research
- Conclusion
- References
- CI
- SE
- ab
- CI
- SE
- ab
- CI
- SE
- ab
- CI
- SE
- ab
- Mediator
- Study 1
- [-0.15, -0.01]
- .03
- -0.07
- [0.10, 0.24]
- .04
- 0.17
- [0.22, 0.39]
- .04
- 0.31
- [0.47, 0.75]
- .07
- 0.60
- Total
- [-0.00, 0.08]
- .02
- 0.04
- [-0.00, 0.06]
- .02
- 0.03
- [0.02, 0.11]
- .02
- 0.06
- [0.01, 0.11]
- .03
- 0.05
- Pos. affect
- [-0.16, -0.05]
- .03
- -0.10
- [0.03, 0.12]
- .02
- 0.07
- [-0.03, 0.05]
- .02
- 0.01
- [0.02, 0.14]
- .03
- 0.08
- Neg. affect
- [-0.07, 0.08]
- .04
- 0.01
- [-0.03, 0.08]
- .03
- 0.02
- [0.09, 0.21]
- .03
- 0.15
- [0.27, 0.49]
- .06
- 0.38
- Trust
- [-0.06, 0.00]
- .01
- -0.03
- [0.02, 0.08]
- .02
- 0.05
- [0.04, 0.14]
- .03
- 0.09
- [0.04, 0.15]
- .03
- 0.09
- Identification
- Study 2
- [-0.32, -0.11]
- .05
- -0.21
- [0.10, 0.34]
- .06
- 0.21
- [0.35, 0.64]
- .07
- 0.49
- [0.62, 1.02]
- .10
- 0.82
- Total
- [-0.09, 0.08]
- .04
- 0.00
- [-0.03, 0.19]
- .05
- 0.08
- [0.07, 0.22]
- .04
- 0.14
- [0.01, 0.26]
- .06
- 0.13
- Pos. affect
- [-0.26, -0.06]
- .05
- -0.15
- [-0.02, 0.14]
- .04
- 0.05
- [-0.15, 0.08]
- .06
- -0.04
- [0.08, 0.40]
- .08
- 0.23
- Neg. affect
- [-0.12, 0.09]
- .05
- -0.02
- [-0.05, 0.17]
- .06
- 0.05
- [0.10, 0.38]
- .07
- 0.24
- [0.21, 0.54]
- .09
- 0.38
- Trust
- [-0.11, 0.02]
- .03
- -0.04
- [-0.04, 0.09]
- .03
- 0.02
- [0.08, 0.24]
- .04
- 0.15
- [-0.02, 0.19]
- .05
- 0.08
- Identification
- Table 5
- Pairwise comparisons of the indirect effects of the moderator groups: Study 1
- Level of Moderator
- SE
- ab
- SE
- ab
- SE
- ab
- SE
- ab
- CI
- CI
- CI
- CI
- Mediator
- [-0.00, 0.08]
- .02
- 0.04
- [-0.00, 0.06]
- .02
- 0.03
- [0.02, 0.11]
- .02
- 0.06
- [0.01, 0.11]
- .03
- 0.05
- Pos. affect
- .04
- .03
- .03
- .04
- [-0.20, -0.05]
- -0.12
- [0.04, 0.15]
- 0.09
- [-0.04, 0.06]
- 0.01
- [0.03, 0.18]
- 0.10
- Human
- [-0.19, -0.05]
- .04
- -0.11
- [0.03, 0.13]
- .03
- 0.08
- [-0.04, 0.06]
- .02
- 0.01
- [0.02, 0.17]
- .04
- 0.09
- Humanoid
- Neg. affect
- .03
- .02
- .01
- .02
- [-0.11, 0.00]
- -0.05
- [-0.00, 0.08]
- 0.03
- [-0.02, 0.03]
- 0.00
- [-0.00, 0.09]
- 0.04
- Android
- [-0.09, 0.11]
- .05
- 0.02
- [-0.04, 0.11]
- .04
- 0.03
- [0.13, 0.30]
- .05
- 0.21
- [0.05, 0.21]
- .04
- 0.12
- Human
- .02
- .02
- [-0.04, 0.05]
- 0.01
- [-0.02, 0.05]
- 0.01
- [0.03, 0.16]
- .03
- 0.09
- [0.01, 0.19]
- .04
- 0.09
- Humanoid
- Trust
- [-0.04, 0.06]
- .02
- 0.01
- [-0.02, 0.05]
- .02
- 0.01
- .03
- [-0.06, 0.12]
- .05
- 0.03
- Android
- [0.04, 0.16]
- 0.09
- Note: N = 229. DA = decision agent; ContrastDA1: 2/3 = human, -1/3 = humanoid, -1/3 = machinelike; ContrastDA2: 0 = human, 1/2 = humanoid, -1/2 = machinelike; Diff. = difference between indirect effects; CI = bias-corrected 95% bootstrap confidence in...
- .02
- [-0.08, 0.00]
- -0.04
- [0.02, 0.12]
- .02
- 0.06
- [0.05, 0.20]
- .04
- 0.12
- [0.39, 0.69]
- .08
- 0.53
- Human
- [-0.07, 0.00]
- .02
- -0.03
- .02
- .04
- .08
- Humanoid
- Identification
- [0.01, 0.10]
- 0.05
- [0.01, 0.18]
- 0.09
- [0.08, 0.39]
- 0.23
- [-0.04, 0.02]
- .01
- -0.01
- [-0.03, 0.07]
- .02
- 0.01
- [-0.06, 0.11]
- .04
- 0.03
- [0.09, 0.38]
- .07
- 0.23
- Android
- Table 5
- Pairwise comparisons of the indirect effects of the moderator groups: Study 1
- Note: N = 229. DA = decision agent; ContrastDA1: 2/3 = human, -1/3 = humanoid, -1/3 = machinelike; ContrastDA2: 0 = human, 1/2 = humanoid, -1/2 = machinelike; Diff. = difference between indirect effects; CI = bias-corrected 95% bootstrap confidence in...
- Table 7
- Pairwise comparisons of the indirect effects of the moderator groups: Study 2
- Table 5
- Pairwise comparisons of the indirect effects of the moderator groups: Study 1
- Note: N = 229. DA = decision agent; ContrastDA1: 2/3 = human, -1/3 = humanoid, -1/3 = machinelike; ContrastDA2: 0 = human, 1/2 = humanoid, -1/2 = machinelike; Diff. = difference between indirect effects; CI = bias-corrected 95% bootstrap confidence in...
- Table 10
- Difference Tests of the Indirect Effects of the Two Alternative Moderators
- Note: N = 132. Index = index of moderated mediation; CI = bias-corrected 95% bootstrap confidence interval, 10,000 bootstrap samples, CIs not including zero are printed in bold.
- Appendix A
- Printed on non-ageing paper ISO 9706
