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Creation of the algorithmic management questionnaire: A six‐phase scale development process.
- Source :
- Human Resource Management; Jan2024, Vol. 63 Issue 1, p25-44, 20p
- Publication Year :
- 2024
-
Abstract
- There is an increasing body of research on algorithmic management (AM), but the field lacks measurement tools to capture workers' experiences of this phenomenon. Based on existing literature, we developed and validated the algorithmic management questionnaire (AMQ) to measure the perceptions of workers regarding their level of exposure to AM. Across three samples (overall n = 1332 gig workers), we show the content, factorial, discriminant, convergent, and predictive validity of the scale. The final 20‐item scale assesses workers' perceived level of exposure to algorithmic: monitoring, goal setting, scheduling, performance rating, and compensation. These dimensions formed a higher order construct assessing overall exposure to algorithmic management, which was found to be, as expected, negatively related to the work characteristics of job autonomy and job complexity and, indirectly, to work engagement. Supplementary analyses revealed that perceptions of exposure to AM reflect the objective presence of AM dimensions beyond individual variations in exposure. Overall, the results suggest the suitability of the AMQ to assess workers' perceived exposure to algorithmic management, which paves the way for further research on the impacts of these rapidly accelerating systems. [ABSTRACT FROM AUTHOR]
- Subjects :
- EXPERIMENTAL design
EMPLOYEE attitudes
RESEARCH evaluation
RESEARCH methodology
RESEARCH methodology evaluation
MATHEMATICAL models
DISCRIMINANT analysis
GOODNESS-of-fit tests
ARTIFICIAL intelligence
JOB involvement
DECISION support systems
CRONBACH'S alpha
CONCEPTUAL structures
RESEARCH funding
AUTONOMY (Psychology)
THEORY
FACTOR analysis
QUESTIONNAIRES
DESCRIPTIVE statistics
SCALE analysis (Psychology)
MANAGEMENT
PREDICTIVE validity
STATISTICAL models
WORKING hours
ALGORITHMS
GOAL (Psychology)
Subjects
Details
- Language :
- English
- ISSN :
- 00904848
- Volume :
- 63
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Human Resource Management
- Publication Type :
- Academic Journal
- Accession number :
- 174603964
- Full Text :
- https://doi.org/10.1002/hrm.22185