Attitudes toward Cooperative Industrial Robots Questionnaire (ACIR-Q)

Abstract

The Attitudes toward Cooperative Industrial Robots Questionnaire (ACIR-Q; Leichtmann et al., 2023) is a diagnostic instrument developed to assess workers’ attitudes towards mobile cooperative manufacturing robots. Its content draws upon established measurement items from Chao and Kozlowski (1986) and Herold, Farmer, and Mobley (1985), with final item selection optimized using ant colony optimization. The ACIR-Q comprises 12 items and was validated using online samples of German manufacturing workers and a field sample from local manufacturing companies. This context-specific questionnaire is designed to inform managerial decisions and interventions regarding the implementation of new robotic technology in the workplace.

Keywords

Affect-Behavior, Ant Colony Optimization, Cooperative Industrial Robots, Employee Attitudes, Manufacturing, Social, Task, Workplace.

Authors

Leichtmann, Benedikt; Hartung, Johanna; Wilhelm, Oliver; Nitsch, Verena

Purpose

The primary purpose of the Attitudes toward Cooperative Industrial Robots Questionnaire (ACIR-Q) is to serve as a diagnostic tool for measuring workers’ attitudes toward mobile cooperative manufacturing robots within specific workplace contexts. This assessment provides a fundamental basis for managerial decisions and interventions concerning the successful implementation of new robotic technology in the workplace. By understanding employee attitudes, organizations can proactively address potential challenges and foster a more positive transition to automated systems.

Validity

Construct Validity: The ACIR-Q demonstrates good construct validity, as evidenced by the results of factor analysis. The analysis supported the presence of three distinct factors, which effectively capture the underlying constructs of attitudes toward robots. This suggests that the questionnaire accurately measures the intended theoretical dimensions of workers’ perceptions.

Test Validity: The test validity of the ACIR-Q was established through rigorous psychometric evaluations. This includes an assessment of how well the test measures what it claims to measure, ensuring that the questionnaire is a suitable tool for its intended purpose of evaluating attitudes toward cooperative industrial robots.

Reliability

Internal Consistency: The ACIR-Q exhibits strong internal consistency. Reliability values (ω) for the scale ranged from .81 to .84, indicating a high degree of coherence among the items within the questionnaire. This suggests that the items consistently measure the same underlying construct, leading to dependable and stable results.

Test Reliability: The overall reliability of the ACIR-Q was assessed through various psychometric analyses, confirming its consistency and dependability as a measurement instrument. This ensures that repeated administrations of the questionnaire under similar conditions would yield comparable results.

Factor Analysis

Exploratory Factor Analysis (EFA): An initial EFA was conducted on the ACIR-Q. This analysis led to the identification of five factors, collectively explaining 42% of the total variance in the data. However, a pressure-related factor was subsequently removed from further analysis due to its low explanatory power (only 3% of variance) and weak factor loadings. This refinement aimed to improve the clarity and interpretability of the factor structure.

Confirmatory Factor Analysis (CFA): Following the EFA, a CFA was performed. The combined results from both exploratory and confirmatory factor analyses strongly indicated that attitudes toward robots can be comprehensively described by three primary factors: affective/behavioral concerns, task-related concerns, and social-related concerns. These factors provide a robust framework for understanding the multifaceted nature of workers’ attitudes towards industrial robots.

Ant Colony Optimization (ACO): Ant Colony Optimization was utilized in the development of the ACIR-Q to optimize the selection of items. This algorithm identified the best solution, resulting in the final 12-item questionnaire. The effectiveness of this optimization was reflected in excellent model fit indices, with a Comparative Fit Index (CFI) approximately equal to 1 and a Root Mean Square Error of Approximation (RMSEA) approximately equal to 0. These values signify a strong fit between the proposed factor structure and the observed data.

Instrument: Attitudes toward Cooperative Industrial Robots Questionnaire (ACIR-Q)

Test Type: Original
Format: Items are rated using a 5-point bi-polar scale.
Language Available: German
Population Group: Human; Male; Female
Age Group: Adulthood (18 yrs & older)
Population Details: The target population consists of manufacturing workers located in Germany.
Test Methodology: The development and validation of the ACIR-Q involved various methodologies, including Test Validity, Construct Validity, Test Reliability, Internal Consistency, Factor Analysis, Confirmatory Factor Analysis, and Exploratory Factor Analysis.

Keywords

Affect-Behavior, Ant Colony Optimization, Cooperative Industrial Robots, Employee Attitudes, Manufacturing, Social, Task, Workplace.

Authors

• Leichtmann, Benedikt

  • Author ORCID Identifier: http://orcid.org/0000-0002-9062-0996

  • Affiliation: Johannes Kepler University Linz, Robopsychology Lab

  • Email address: [email protected]

  • Correspondence Address: Johannes Kepler University Linz, Robopsychology Lab, Altenberger Str. 69, Linz, Austria, 4040, [email protected]

• Hartung, Johanna

  • Author ORCID Identifier: http://orcid.org/0000-0002-6392-4468

  • Affiliation: University of Bonn, Department of Psychology

  • Email address: [email protected]

• Wilhelm, Oliver

  • Author ORCID Identifier: http://orcid.org/0000-0001-7980-1166

  • Affiliation: Ulm University, Institute of Psychology and Education

  • Email address: [email protected]

• Nitsch, Verena

  • Affiliation: RWTH Aachen University, Institute of Industrial Engineering and Ergonomics

  • Email address: [email protected]

Permissions & Fee and Test Year

Permissions: The Attitudes toward Cooperative Industrial Robots Questionnaire (ACIR-Q) may be used for research and teaching purposes. The specific licensing details are available at http://creativecommons.org/licenses/by/4.0/ and supplementary materials can be found at https://osf.io/5fnr9/.

Fee: No fee is required for the use of this instrument. It is commercially not available.

Test Year: 2023

References

Leichtmann, B., Hartung, J., Wilhelm, O., & Nitsch, V. (2023). New short scale to measure workers’ attitudes toward the implementation of cooperative robots in industrial work settings: Instrument development and exploration of attitude structure. International Journal of Social Robotics, 15(6), 909–930. https://doi.org/10.1007/s12369-023-00996-0

Items of the Attitudes toward Cooperative Industrial Robots Questionnaire (ACIR-Q)

The ACIR-Q consists of 12 items. While the specific content of each item is not provided in detail, the subscales identified are: Task beliefs, Social beliefs, and Affect-Behavior. The items are available in English and German and are rated using a 5-point bi-polar scale. The items are accessible in Appendix C, Pages 924-925 of the source reference.

Attitudes toward Cooperative Industrial Robots Questionnaire (ACIR-Q)

The codes in this table are the codes used in this paper. The column “Factors” indicates the corresponding factor.

Instructions for Responses

In the following, you will find statements about robots and their effects on your work. In each line, you will find two opposing statements at the respective ends. Please indicate for each line which of the two statements you rather agree with by putting a cross between the statements. The more you agree with a statement, the closer your cross should be to that statement. We are interested in your personal opinion. There are no right or wrong answers. So please answer honestly.

• Affect/Behavior = {attitudes1.5, attitudes5.3, attitudes7.4, attitudes7.9}

• Task = {attitudes4.1, attitudes5.8, attitudes6.3, attitudes6.5}

• Social = {attitudes3.4, attitudes3.6, attitudes3.8, attitudes3.10}