Algorithmic Management Questionnaire

Abstract

The Algorithmic Management Questionnaire (AMQ), developed by Parent-Rocheleau et al. in 2024, is a specialized psychometric instrument designed to quantify workers’ subjective exposure to algorithmic management (AM) functions within the workplace. Utilizing a rigorous deductive approach, the scale development process ensured strong theoretical grounding by reviewing existing literature on core AM functions, including monitoring, goal setting, scheduling, performance rating, and compensation. Starting with an initial pool of 36 items, the measure was refined through content validity analysis and subsequent factor analyses across three independent participant samples, resulting in a final 20-item instrument demonstrating strong psychometric properties regarding both reliability and validity.

Keywords

Algorithmic Management, Algorithmic Control, Employee Perceptions, Monitoring, Goal Setting, Scheduling, Performance Rating, Compensation, Factorial Validity, Human Resource Management, Organizational Measures.

Authors

Parent-Rocheleau, Xavier, Parker, Sharon K., Bujold, Antoine, Gaudet, Marie-Claude.

Purpose

The primary purpose of the AMQ is to systematically evaluate the degree to which employees perceive themselves to be under the control or influence of algorithmic management systems. It specifically captures perceived exposure across critical organizational domains where automated decision-making processes are frequently implemented.

The instrument provides researchers and practitioners with a standardized, validated tool to measure this emerging phenomenon, allowing for the investigation of its downstream effects on worker attitudes, well-being, and job characteristics, such as job autonomy and complexity.

Construct

The AMQ measures the overarching constructs of Algorithmic Control and Algorithmic Management. These constructs refer to the use of data-driven, automated systems—often mediated by software or artificial intelligence—to manage, organize, evaluate, and discipline human labor.

The scale operationalizes this broad construct through five distinct, yet related, sub-dimensions, reflecting the functional areas where algorithmic systems exert influence: Monitoring, Goal Setting, Scheduling, Performance Rating, and Compensation.

Validity

The development of the AMQ included comprehensive validation procedures to ensure the scale accurately measures the intended constructs.

• Content Validity: This was established early in the development process. Items were rigorously evaluated against literature-based criteria and refined to ensure they were meaningful and relevant to the defined functions of algorithmic management in real-world workplace settings.
• Discriminant Validity: Evidence for discriminant validity was confirmed by low correlations (ranging from 0.03 to 0.22) between the AM function subscales and an external criterion variable, demonstrating that the AMQ measures a distinct concept separate from other established workplace metrics.
• Convergent Validity: The scale showed moderate to high correlations with related variables, specifically system usefulness (0.43 to 0.53) and ease of use (0.35 to 0.43), supporting its theoretical link to perceptions of technological systems.
• Predictive Validity: The AMQ demonstrated strong predictive power. Exposure to algorithmic management measured at Time 1 significantly and negatively predicted later measures of job autonomy (β = -0.24, p < 0.01) and job complexity (β = -0.26, p < 0.01), aligning with theoretical predictions regarding the restrictive nature of algorithmic control.

Reliability

The internal consistency of the Algorithmic Management Questionnaire was assessed using Cronbach’s alpha across its five dimensions. The results indicated strong reliability across all factors, with alpha coefficients consistently ranging from 0.810 to 0.907. These high values confirm that the items within each subscale reliably measure the same underlying dimension of algorithmic management exposure.

Factor Analysis

The factorial structure of the AMQ was confirmed using Confirmatory Factor Analysis (CFA) across multiple independent samples, substantiating the hypothesized five-factor structure (Monitoring, Goal Setting, Scheduling, Performance Rating, and Compensation).

The initial CFA model (Sample 1) demonstrated excellent fit statistics: χ²(162) = 346.8, CFI = 0.975, TLI = 0.971, RMSEA = 0.048, and SRMR = 0.044. These values indicate a superior fit of the model to the observed data. A subsequent replication sample further confirmed the robustness of this structure, yielding similarly strong fit indices: χ²(161) = 300.29, CFI = 0.968, TLI = 0.962, RMSEA = 0.049, and SRMR = 0.052.

Instrument

Test Type: Original Inventory/Questionnaire

Format: Participants respond to 20 items using a seven-point Likert scale, anchored by 1 (completely disagree) and 7 (strongly agree). The administration method is electronic.

Language Available: English (Original)

Population Group: Human (Male and Female)

Age Group: Adulthood (18+), including Young Adulthood (18-29) and Thirties (30-39).

Population Details: The initial psychometric validation was conducted using participants recruited via Mechanical Turk.

Test Methodology: Test Validity; Content Validity; Convergent Validity; Discriminant Validity; Predictive Validity; Test Reliability; Internal Consistency; Factor Analysis; Confirmatory Factor Analysis.

Keywords

Automation, Algorithmic Decision-Making, Employee Attitudes, Factorial Validity, Job Performance, Management Methods, Optimization Algorithms, Organizational and Occupational Measures, Work Scheduling.

Authors

Author ORCID Identifier:

• Parent-Rocheleau, Xavier: 0000-0001-5015-3214 (HEC Montreal)
• Parker, Sharon K.: 0000-0002-0978-1873 (Curtin University Centre for Transformative Work Design)
• Bujold, Antoine: 0000-0002-6784-4895 (HEC Montreal)
• Gaudet, Marie-Claude (HEC Montreal)

Affiliation Email addresses: The primary corresponding author email is [email protected].

Correspondence Address: Parent-Rocheleau, Xavier: HEC Montreal, Montreal, Quebec, Canada.

Permissions & Fee and Test Year

The Algorithmic Management Questionnaire (AMQ) was published in 2024. Information regarding specific permissions and fees for commercial use must be obtained directly from the corresponding author, Xavier Parent-Rocheleau, or the publishing journal, Human Resource Management.

Test Year: 2024

Reference’s

1. Parent‐Rocheleau, X., Parker, S. K., Bujold, A., & Gaudet, M.‐C. (2024). Creation of the Algorithmic Management Questionnaire: A six‐phase scale development process. Human Resource Management, 63(1), 25–44. DOI: https://doi.org/10.1002/hrm.22185
2. Hinkin, T. R. (1998). A brief tutorial on the development of measures for use in survey questionnaires. Organizational Research Methods, 1(1), 104–121.
3. Lehdonvirta, V. (2018). The management of crowds: Algorithmic management and the future of work. In P. Drahokoupil (Ed.), The platform economy and the digital transformation of work (pp. 57–71). European Trade Union Institute.
4. Möhlmann, M., Zalmanson, L., Henfridsson, O., & Parker, G. G. (2021). Algorithmic management and employee well-being in the gig economy: A mediated model. MIS Quarterly, 45(4), 1845–1868.
5. Rahman, M. (2021). Algorithmic management in the platform economy: A comprehensive literature review. Journal of Business Research, 137, 355–367.
6. Wood, A. J., Graham, M., & Martin, G. (2019). Good gig, bad gig: Autonomy and algorithmic control in the gig economy. Work, Employment and Society, 33(1), 56–75.

Items of the Algorithmic Management Questionnaire

IMPORTANT: The following scale items must be preserved in their original language and must not be changed in any way.

The specific 20 items that comprise the Algorithmic Management Questionnaire (AMQ) were not provided in the initial source data. The scale is structured around five subscales, with four items dedicated to each function:

• Monitoring
• Goal Setting
• Scheduling
• Performance Rating
• Compensation