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Which Factors Influence Laboratory Employees’ Acceptance of Laboratory 4.0 Systems?

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Human-Technology Interaction

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Abstract

Laboratory 4.0 systems provide a central ecosystem in the lab that connects people, processes, devices, and environmental data, comparable to the concept of smart home. Laboratory 4.0 enables laboratory employees to organize their lab and allows users to combine products from different vendors to create their personal laboratory infrastructure. Contrary to the field of smart home, to our knowledge, there is no study investigating the laboratory employees’ acceptance and intention to use the technology of laboratory 4.0. Therefore, this study aims to examine the factors which influence the acceptance of laboratory 4.0 of potential users by applying the technology acceptance model (TAM) adopted from smart home. Partial least squares—structural equation modeling (PLSSEM) was used to describe the TAM and extended by trust and perceived risk, which pose potentially important factors for users in the sensitive field of laboratory data. The results revealed that users’ attitude toward laboratory 4.0 is heavily affected by users’ perceived usefulness which, in turn, impacts the intention to use laboratory 4.0. By determining the total effects, perceived usefulness is the most important factor influencing attitude toward and intention to use laboratory 4.0. In comparison to smart home, attitude toward use and perceived usefulness seem especially important in the context of laboratory 4.0 and appear to play a decisive role regarding the establishment of this infrastructure. The current study can serve as a foundation for future research on improving laboratory 4.0 systems by considering the relevance of influencing factors on user acceptance.

Supported by Fraunhofer Institute for Manufacturing Engineering and Automation IPA.

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Acknowledgments

Thank you to Andrea Siegberg and her C9 Information management team (Fraunhofer Cooperation) for assisting with the questionnaire. Special thanks to Ms. Sabine Lauderbach for her knowledge of statistics.

Author information

Authors and Affiliations

  1. Hochschule Rhein-Waal, University of Applied Sciences, Kamp-Lintfort, Germany

    Sarah Polzer & Karsten Nebe

  2. Fraunhofer Institute for Manufacturing Engineering and Automation IPA, Stuttgart, Germany

    Milena Frahm & Matthias Freundel

Authors
  1. Sarah Polzer
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  2. Milena Frahm
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  3. Matthias Freundel
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  4. Karsten Nebe
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Corresponding author

Correspondence to Sarah Polzer .

Editor information

Editors and Affiliations

  1. Institute Industrial IT, OWL University of Applied Sciences and Arts, Lemgo, Germany

    Carsten Röcker

  2. Institute Industrial IT, OWL University of Applied Sciences and Arts, Lemgo, Germany, Human-Centered Information Systems, Clausthal University of Technology, Clausthal-Zellerfeld, Germany

    Sebastian Büttner

Appendices

Appendices

12.1.1 Appendix 1: Questionnaire Items Used in the Survey

A table with 2 columns of construct and description has multiple rows. The factors listed in the table include perceived usefulness, perceived ease of use, attitude toward the lab, intention to use, trust, and perceived risk.

12.1.2 Appendix 2: Laboratory 4.0 Model

A flow diagram of the laboratory 4.0 model connects perceived risk with trust, attitude toward lab 4.0, intention to use, ease of use, and usefulness flows to attitude towards lab 4.0.

12.1.3 Appendix 3: Discriminant Validity: Fornell-Larcker Criterion

A table of the discriminant validity of the Fornell Larcker criterion with 6 rows and columns. The column and row headers are attitude, ease of use, intention, risk, trust, and usefulness.

12.1.4 Appendix 4: Discriminant Validity: Outer Loadings/Cross-Loadings

A table of the discriminant validity of outer loading with 6 columns and 20 rows. The attitude, ease of use, intention, risk, trust, and usefulness.

12.1.5 Appendix 5: Collinearity Statistics (VIF)

A table of the collinearity statistics with 6 columns and 6 rows. The column and row headers are attitude, ease of use, intention, risk, trust, and usefulness.

12.1.6 Appendix 6: Influence Paths and Hypotheses Results

A table of the influence paths and hypotheses results with 4 columns and 8 rows. The column headers are the original sample, t statistics, p values, and results. The row has a hypothesis path of H 1 to H 8.

12.1.7 Appendix 7: Total Effects

A table of the total effects with 6 columns and 6 rows. The column and row headers are attitude, ease of use, intention, risk, trust, and usefulness.

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Polzer, S., Frahm, M., Freundel, M., Nebe, K. (2023). Which Factors Influence Laboratory Employees’ Acceptance of Laboratory 4.0 Systems?. In: Röcker, C., Büttner, S. (eds) Human-Technology Interaction. Springer, Cham. https://doi.org/10.1007/978-3-030-99235-4_12

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  • DOI: https://doi.org/10.1007/978-3-030-99235-4_12

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  • Online ISBN: 978-3-030-99235-4

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