Journal of Technology Development Management

Journal of Technology Development Management

The Impact of Anthropomorphism of Collaborative Robots on Their Acceptance in the Automotive Industry: The Mediating Role of Perceived Safety

Document Type : Research Paper

Author
HamidReza Talaie
Department of Industrial Management, Faculty of Administrative Sciences and Economics, Arak University, Arak, Iran.
10.22104/jtdm.2026.7788.3440
Abstract
This study examines the anthropomorphism of collaborative robots and its impact on perceived competence, perceived safety, perceived threat, and, ultimately, employee acceptance of these robots in the automotive industry. The research is applied, descriptive-correlational, and cross-sectional. The statistical population comprises employees in the automotive industry, from whom 384 individuals were randomly selected. The measurement model’s reliability and validity were confirmed using Cronbach’s alpha, composite reliability, AVE, cross-loadings, and the HTMT criterion. To test the mediating effects, mediation analysis was conducted, and the VAF index was calculated. Statistical analysis was conducted using structural equation modeling (SEM). The findings revealed that the anthropomorphic design of collaborative robots positively influences perceived safety and perceived competence, while it may also increase perceived threat. Nonetheless, perceived safety plays a significant role in the acceptance of collaborative robots and can amplify the impact of anthropomorphic design. The acceptance of collaborative robots remains a relatively new area of research and has not yet been thoroughly explored, particularly in the Iranian context. Results suggest that improving acceptance of collaborative robots requires reducing perceived threat and enhancing safety in their design.
Keywords
Anthropomorphism of collaborative robots
Acceptance of collaborative robots
Perceived competence
Perceived threat
Perceived safety
Subjects
AlNuaimi, B. K., Khan, M., & Ajmal, M. M. (2021). The role of big data analytics capabilities in greening e-procurement: A higher order PLS-SEM analysis. Technological Forecasting and Social Change, 169, 120808. https://doi.org/10.1016/j.techfore.2021.120808
Appel, M., Izydorczyk, D., Weber, S., Mara, M., & Lischetzke, T. (2020). The uncanny of mind in a machine: Humanoid robots as tools, agents, and experiencers. Computers in Human Behavior, 102, 274-286.
Baumgartner, M., Kopp, T., & Kinkel, S. (2022). Analysing factory workers’ acceptance of collaborative robots: a web-based tool for company representatives. Electronics, 11(1), 145.
Cohen, Y., Shoval, S., Faccio, M., & Minto, R. (2022). Deploying cobots in collaborative systems: major considerations and productivity analysis. International Journal of Production Research, 60(6), 1815-1831.
Cusano, N. (2023). Cobot and Sobot: for a new ontology of collaborative and social robots. Foundations of Science, 28(4), 1143-1155.
Esmaeili`, A., Ghazinoori, S., Naghizadeh, M., Bamdad Soufi, J. and Manteghi, M. (2021). Operational Capabilities as One of the Preconditions for Presence in the Global Supply Network of the Autoparts Industry; A Multi-case AnalysisOperations Capabilities as One of the Preconditions to Join Global Supply Network of Autoparts Industry: A Multiple Case Analysis. Journal of Technology Development Management, 9(1), 95-133. doi: 10.22104/jtdm.2021.4661.2750 [In Persian].
Gualtieri, L., Rauch, E., & Vidoni, R. (2021). Emerging research fields in safety and ergonomics in industrial collaborative robotics: A systematic literature review. Robotics and Computer-Integrated Manufacturing, 67, 101998.
Guertler, M., Tomidei, L., Sick, N., Carmichael, M., Paul, G., Wambsganss, A., ... & Hussain, S. (2023). When is a robot a cobot? Moving beyond manufacturing and arm-based cobot manipulators. Proceedings of the Design Society, 3, 3889-3898.
Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., Ray, S., ... & Ray, S. (2021). An introduction to structural equation modeling. Partial least squares structural equation modeling (PLS-SEM) using R: a workbook, 1-29. https://doi.org/10.1007/978-3-030-80519-7_1
Javaid, M., Haleem, A., Singh, R. P., Rab, S., & Suman, R. (2022). Significant applications of Cobots in the field of manufacturing. Cognitive Robotics, 2, 222-233.
Khatami Firouzabadi, S. M. A., Tabatabaeian, S. H. and Dashti, M. A. (2019). Key success factors in the process of implementing advanced technologies in the industrial firms: Pieces of evidence from the automotive industry in Iran. Journal of Technology Development Management, 6(4), 89-126. doi: 10.22104/jtdm.2019.3000.2013 [In Persian].
Klebbe, R., & Friese, C. (2025). Exploring the Role of Robots in Inpatient Care: Caregivers´ Perspectives on the Development and Evaluation of Collaborative Robot Applications–A Qualitative Research Approach. International Journal of Social Robotics, 1-18.
Kopp, T., Baumgartner, M., & Kinkel, S. (2022). How linguistic framing affects factory workers' initial trust in collaborative robots: The interplay between anthropomorphism and technological replacement. International Journal of Human-Computer Studies, 158, 102730.
Kraus, J., Miller, L., Klumpp, M., Babel, F., Scholz, D., Merger, J., & Baumann, M. (2024). On the role of beliefs and trust for the intention to use service robots: an integrated trustworthiness beliefs model for robot acceptance. International Journal of Social Robotics, 16(6), 1223-1246.
Law, L., & Fong, N. (2020). Applying partial least squares structural equation modeling (PLS-SEM) in an investigation of undergraduate students’ learning transfer of academic English. Journal of English for Academic Purposes, 46, 100884. https://doi.org/10.1016/j.jeap.2020.100884.
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.
Liao, S., Lin, L., & Chen, Q. (2023). Research on the acceptance of collaborative robots for the industry 5.0 era--the mediating effect of perceived competence and the moderating effect of robot use self-efficacy. International Journal of Industrial Ergonomics, 95, 103455.
Liao, S., Lin, L., Chen, Q., & Pei, H. (2024). Why not work with anthropomorphic collaborative robots? The mediation effect of perceived intelligence and the moderation effect of self‐efficacy. Human Factors and Ergonomics in Manufacturing & Service Industries, 34(3), 241-260.
Liao, S., Chen, C., Yao, Y., & Chen, Q. (2024). Would You be Willing to Share Knowledge with a Collaborative Robot? The Mediating Effect of Perceived Agency and the Moderating Effect of Identity Threat. International Journal of Human–Computer Interaction, 1-26.
Liu, L., Zou, Z., & Greene, R. L. (2024). The effects of type and form of collaborative robots in manufacturing on trustworthiness, risk perceived, and acceptance. International Journal of Human–Computer Interaction, 40(10), 2697-2710.
Lutin, E., Elprama, S. A., Cornelis, J., Leconte, P., Van Doninck, B., Witters, M., ... & Jacobs, A. (2024). Pilot Study on the Relationship Between Acceptance of Collaborative Robots and Stress. International Journal of Social Robotics, 16(6), 1475-1488.
Paliga, M. (2022). Human–cobot interaction fluency and cobot operators’ job performance. The mediating role of work engagement: A survey. Robotics and Autonomous Systems, 155, 104191.
Prassida, G. F., & Asfari, U. (2022). A conceptual model for the acceptance of collaborative robots in industry 5.0. Procedia Computer Science, 197, 61-67.
Rashmei, M. H., Hosseini Shakib, M. and Khamseh, A. (2023). The pattern of Industry 4.0 technologies adoption in Iran's auto parts manufacturing companies. Journal of Technology Development Management, 11(3), 169-210. doi: 10.22104/jtdm.2024.6743.3274 [In Persian].
Taesi, C., Aggogeri, F., & Pellegrini, N. (2023). COBOT applications—recent advances and challenges. Robotics, 12(3), 79.
Talaie, H. (2025). The Role of Industry 5.0 in Mitigating Supply Chain Risks and Boosting Performance: A Pathway to Sustainable Competitive Advantage. Strategic Value Chain Management, 2(4), 55-80. doi: 10.22075/svcm.2025.39107.1052 [In Persian].

  • Receive Date 31 July 2025
  • Revise Date 15 March 2026
  • Accept Date 23 March 2026