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Mapping Stakeholder Perceptions: Navigating Biometric Data Protection Initiative and Face Recognition Technology Support in Indonesia
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References

  • 2019A systematic review of algorithm aversion in augmented decision making809 cited
  • 2018The European Union General Data Protection Regulation: What It Is And What It Means796 cited
  • 2020Discriminated by an algorithm: a systematic review of discrimination and fairness by algorithmic decision-making in the context of HR recruitment and HR development509 cited
  • 2022Fairness perceptions of algorithmic decision-making: A systematic review of the empirical literature316 cited
  • 2023Attaining Sustainable Development Goals through Financial Inclusion: Exploring Collaborative Approaches to Fintech Adoption in Developing Economies186 cited
  • 2022Are Algorithmic Decisions Legitimate? The Effect of Process and Outcomes on Perceptions of Legitimacy of AI Decisions135 cited
  • 2019Race, again: how face recognition technology reinforces racial discrimination96 cited
  • 2020‘I’m still the master of the machine.’ Internet users’ awareness of algorithmic decision-making and their perception of its effect on their autonomy95 cited
  • 2022An integrative model of facial recognition check-in technology adoption intention: the perspective of hotel guests in Singapore78 cited
  • 2020THE DEVELOPMENT AND VALIDATION OF THE PENTA HELIX CONSTRUCT77 cited
  • 2022Positive and negative valences, personal innovativeness and intention to use facial recognition for payments72 cited
  • 2004Ethical aspects of facial recognition systems in public places67 cited
  • 2023Pursuing Long-Term Business Performance: Investigating the Effects of Financial and Technological Factors on Digital Adoption to Leverage SME Performance and Business Sustainability—Evidence from Indonesian SMEs in the Traditional Market

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65 cited
  • 2020Facial recognition check-in services at hotels56 cited
  • 2022Resistance of facial recognition payment service: a mixed method approach55 cited
  • 2022“So how do we balance all of these needs?”: how the concept of AI technology impacts digital archival expertise50 cited
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