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The Care-Dependent are Less Averse to Care Robots: Comparing Intuitions of the Affected and the Non-Affected

Author

Listed:
  • Manuela Schönmann

    (Faculty of Computer Science, Technische Hochschule Ingolstadt, Ingolstadt, Germany; TUM School of Social Sciences and Technology, Technical University of Munich, Munich, Germany)

  • Anja Bodenschatz

    (Faculty of Computer Science, Technische Hochschule Ingolstadt, Ingolstadt, Germany; TUM School of Social Sciences and Technology, Technical University of Munich, Munich, Germany; Seminar for Corporate Development and Business Ethics, Faculty of Management, Economics and Social Sciences, University of Cologne, Cologne, Germany)

  • Matthias Uhl

    (Faculty of Computer Science, Technische Hochschule Ingolstadt, Ingolstadt, Germany; TUM School of Social Sciences and Technology, Technical University of Munich, Munich, Germany)

  • Gari Walkowitz

    (Faculty of Business Administration, Technische Universität Bergakademie Freiberg, Freiberg, Germany)

Abstract

The world’s population will continue to age significantly in the near future. One strategy to address the growing gap between supply and demand of professional caregivers in many regions is the use of care robots. Although there have been numerous ethical debates about the use of robots in elderly care, the important question of how (potentially) affected people perceive situations with care robots compared to situations with human caregivers has not yet been systematically examined. Using a large-scale experimental vignette study, we investigated the influence of the nature of the caregiver on participants’ perceived well-being when confronted with different care situations in nursing homes. Our results show that the views of people already affected by care dependency regarding care robots differ substantially from the views of people not affected by care dependency. The non-affected strongly devalued care robots compared to human caregivers, especially in a service context. This devaluation was not found among those affected; their perceived well-being was not influenced by the nature of the caregiver. These findings also proved robust when controlling for people’s attitudes toward robots, gender, and age.

Suggested Citation

  • Manuela Schönmann & Anja Bodenschatz & Matthias Uhl & Gari Walkowitz, 2022. "The Care-Dependent are Less Averse to Care Robots: Comparing Intuitions of the Affected and the Non-Affected," Munich Papers in Political Economy 24, Munich School of Politics and Public Policy and the School of Management at the Technical University of Munich.
  • Handle: RePEc:aiw:wpaper:24
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    References listed on IDEAS

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    Keywords

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    JEL classification:

    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being

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