Exploring Stakeholder Acceptance of Workplace Personalization

  • Joshua Duvnjak*
  • , Ayse Kucukyilmaz
  • , Robert J. Houghton
  • , David R. Large
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Personalization in the workplace may be used to support workers by simplifying tasks or reducing workload, but requires the collection of personal data, and this raises concerns over privacy and possible discrimination if applied indiscriminately. The study explored the factors associated with acceptance of three types of workplace personalization system (Suggester, Swappers and Controller, within-subjects) and two personal data types (Heart Rate, Performance, between-subjects) by presenting vignettes using an online experimental platform (Prolific.com) and capturing respondents' (n = 204) attitudes using recognized acceptance questionnaires (e.g., the Advanced Transport Telematics Acceptance Assessment, [ATTAA]). Results show acceptance is influenced by the type of personalization system, particularly when physiological (heart rate) data is used, with “Swapper” systems receiving the highest ratings for “Usefulness” and “Satisfying” (interpreted as higher acceptance) compared to suggesters and controllers. Acceptance ratings were not significantly different between personalization types when performance data were used. The Affinity for Technology (AFT) and Need for Cognition (NFC) scales were used to categorize participant characteristics, but only revealed significant differences associated with NFC and usefulness—most notably when using performance data. Overall, the results support the need to consider the type of intervention and the type/amount of personal data required when designing and implementing workplace personalization systems and highlight a particular need for caution when physiological data is required.

Original languageEnglish
Article numbere70030
JournalHuman Factors and Ergonomics in Manufacturing and Service Industries
Volume36
Issue number2
Early online date1 Feb 2026
DOIs
Publication statusPublished - Mar 2026

Keywords

  • acceptance
  • experimental study
  • manufacturing
  • personal data
  • personalization

ASJC Scopus subject areas

  • Human Factors and Ergonomics
  • Industrial and Manufacturing Engineering

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