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Employee Acceptability of Wearable Mental Workload Monitoring in Industry 4.0: A Pilot Study on Motivational and Contextual Framing

Part of: Industry 4.0

Published online by Cambridge University Press:  26 July 2019

Bram B. Van Acker ,
Peter Conradie ,
Peter Vlerick  and
Jelle Saldien
Bram B. Van Acker
Affiliation:
Ghent University, Belgium; Research group IMEC-MICT-Ghent University, Belgium
Peter Conradie
Affiliation:
Ghent University, Belgium; Research group IMEC-MICT-Ghent University, Belgium
Peter Vlerick
Affiliation:
Ghent University, Belgium;
Jelle Saldien
Affiliation:
Ghent University, Belgium; Research group IMEC-MICT-Ghent University, Belgium

Abstract

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As Industry 4.0 will greatly challenge employee mental workload (MWL), research on objective wearable MWL-monitoring is in high demand. However, numerous research lines validating such technology might become redundant when employees eventually object to its implementation. In a pilot study, we manipulated two ways in which employees might perceive MWL-monitoring initiatives. We found that framing the technology in terms of serving intrinsic goals (e.g., improving health) together with an autonomy-supportive context (e.g., allowing discussion) yields higher user acceptability when compared to framing in terms of extrinsic goals (e.g., increasing productivity) together with a controlling context (e.g., mandating use). User acceptability still panned out neutral in case of the former, however - feeding into our own and suggested future work.

Keywords

Wearable mental workload monitoringIndustry 4.0Organizational processesTechnologyUser acceptability
Type
Article
Information
Proceedings of the Design Society: International Conference on Engineering Design , Volume 1 , Issue 1 , July 2019 , pp. 2101 - 2110
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s) 2019

References

Alder, G.S. (2001), “Employee reactions to electronic performance monitoring: A consequence of organizational culture”, The Journal of High Technology Management Research, Vol. 12 No. 2, pp. 323–342. http://doi.org/10.1016/S1047-8310(01)00042-6Google Scholar
Baard, P.P., Deci, E.L. and Ryan, R.M. (2000), “Intrinsic need satisfaction as a motivational basis of performance and well-being at work”, Unpublished Manuscript, Fordham University.Google Scholar
D'Addona, D.M., Bracco, F., Bettoni, A., Nishino, N., Carpanzano, E. and Bruzzone, A.A. (2018), “Adaptive automation and human factors in manufacturing: An experimental assessment for a cognitive approach”, CIRP Annals, CIRP, Vol. 67 No. 1, pp. 455–458. http://doi.org/10.1016/j.cirp.2018.04.123Google Scholar
Deci, E.L., Olafsen, A.H. and Ryan, R.M. (2017), “Self-Determination Theory in Work Organizations: The State of a Science”, Annual Review of Organizational Psychology and Organizational Behavior, Vol. 4 No. 1, pp. 19–43. http://doi.org/10.1146/annurev-orgpsych-032516-113108Google Scholar
Deci, E.L. and Ryan, R.M. (2000), “The ‘What’ and ‘Why’ of Goal Pursuits: Human Needs and the Self-Determination of Behavior”, Psychological Inquiry, Vol. 11 No. 4, pp. 227–268. https://doi.org/10.1207/S15327965PLI1104_01Google Scholar
Kasser, T. and Ryan, R.M. (1996), “Further Examining the American Dream: Differential Correlates of Intrinsic and Extrinsic Goals”, Personality and Social Psychology Bulletin, Vol. 22 No. 3, pp. 280–287. https://doi.org/10.1177/0146167296223006Google Scholar
Longo, F., Nicoletti, L. and Padovano, A. (2017), “Smart operators in industry 4.0: A human-centered approach to enhance operators’ capabilities and competencies within the new smart factory context”, Computers and Industrial Engineering, Vol. 113, pp. 144–159. http://doi.org/10.1016/j.cie.2017.09.016Google Scholar
Gao, Y., Li, H. and Luo, Y. (2015), “An empirical study of wearable technology acceptance in healthcare”, Industrial Management & Data Systems, Vol. 115 No. 9, pp. 1704–1723. https://doi.org/10.1108/IMDS-03-2015-0087Google Scholar
Matthews, G. (2016), “Multidimensional profiling of task stress states for human factors: A brief review”, Human Factors: The Journal of the Human Factors and Ergonomics Society, Vol. 58 No. 6, pp. 801–813. http://doi.org/10.1177/0018720816653688Google Scholar
Mitchell, J.I., Gagné, M., Beaudry, A. and Dyer, L. (2012), “The role of perceived organizational support, distributive justice and motivation in reactions to new information technology”, Computers in Human Behavior, Vol. 28 No. 2, pp. 729–738. http://doi.org/10.1016/j.chb.2011.11.021Google Scholar
Oreg, S. (2006), “Personality, context, and resistance to organizational change”, European Journal of Work and Organizational Psychology, Vol. 15 No. 1, pp. 73–101. https://doi.org/10.1080/13594320500451247Google Scholar
Parasuraman, A. and Colby, C.L. (2015), “An Updated and Streamlined Technology Readiness Index: TRI 2.0”, Journal of Service Research, Vol. 18 No. 1, pp. 59–74. http://doi.org/10.1177/1094670514539730Google Scholar
Prasad, J. and Agarwal, R. (1997), “The Role of Innovation Characteristics and Perceived Voluntariness in the Acceptance of Information Technologies”, Decision Sciences, Vol. 28 No. 3, pp. 557–582. http://doi.org/10.1111/j.1540-5915.1997.tb01322.xGoogle Scholar
Rigby, C.S. and Ryan, R.M. (2018), “Self-Determination Theory in Human Resource Development: New Directions and Practical Considerations”, Advances in Developing Human Resources, Vol. 20 No. 2, pp. 133–147. http://doi.org/10.1177/1523422318756954Google Scholar
Roche, M. and Haar, J.M. (2013), “A metamodel approach towards self-determination theory: A study of New Zealand managers’ organisational citizenship behaviours”, International Journal of Human Resource Management, Vol. 24 No. 18, pp. 3397–3417. http://doi.org/10.1080/09585192.2013.770779Google Scholar
Rupp, M.A., Michaelis, J.R., Mcconnell, D.S. and Smither, J.A. (2016), “The Impact of Technological Trust and Self-Determined Motivation on Intentions to use Wearable Fitness Technology; The Impact of Technological Trust and Self-Determined Motivation on Intentions to use Wearable Fitness Technology”, Proceedings of the Human Factors and Ergonomics Society, pp. 1434–1438.Google Scholar
Ryan, R. and Deci, E. (2000), “Self-determination theory and the facilitation of intrinsic motivation”, American Psychologist, Vol. 55 No. 1, pp. 68–78. http://doi.org/10.1037/0003-066X.55.1.68Google Scholar
Sarpong, S. and Rees, D. (2014), “Assessing the effects of ‘big brother’ in a workplace: The case of WAST”, European Management Journal, Vol. 32 No. 2, pp. 216–222. http://doi.org/10.1016/j.emj.2013.06.008Google Scholar
Schall, M.C., Sesek, R.F. and Cavuoto, L.A. (2018), “Barriers to the Adoption of Wearable Sensors in the Workplace: A Survey of Occupational Safety and Health Professionals”, Human Factors, Vol. 60 No. 3, pp. 351–362. http://doi.org/10.1177/0018720817753907Google Scholar
Sparrow, P.R. (2001), “Developing diagnostics for high performance organization cultures”, in Cooper, C.L., Cartwright, S. and Earley, P.C. (Eds.), The International Handbook of Organizational Culture and Climate, Wiley, Chichester, pp. 85–106.Google Scholar
Van Acker, B.B., Parmentier, D.D., Vlerick, P. and Saldien, J. (2018), “Understanding mental workload: From a clarifying concept analysis toward an implementable framework”, Cognition, Technology & Work, Springer, London, Vol. 20 No. 3, pp. 351–365. http://doi.org/10.1007/s10111-018-0481-3Google Scholar
Van den Broeck, A., Van Ruysseveldt, J., Smulders, P. and De Witte, H. (2011), “Does an intrinsic work value orientation strengthen the impact of job resources? A perspective from the Job Demands–Resources Model”, European Journal of Work and Organizational Psychology, Vol. 20 No. 5, pp. 581–609. http://doi.org/10.1080/13594321003669053Google Scholar
Vansteenkiste, M., Neyrinck, B., Niemiec, C.P., Soenens, B., Witte, H. and Broeck, A. (2007), “On the relations among work value orientations, psychological need satisfaction and job outcomes: A self-determination theory approach”, Journal of Occupational and Organizational Psychology, Vol. 80 No. 2, pp. 251–277. http://doi.org/10.1348/096317906X111024Google Scholar
Vansteenkiste, M., Simons, J., Lens, W., Sheldon, K.M. and Deci, E.L. (2004), “Motivating learning, performance, and persistence: The synergistic effects of intrinsic goal contents and autonomy-supportive contexts”, Journal of Personality and Social Psychology, Vol. 87 No. 2, pp. 246–260. http://doi.org/10.1037/0022-3514.87.2.246Google Scholar
Vansteenkiste, M., Simons, J., Lens, W., Soenens, B. and Matos, L. (2005), “Examining the impact of intrinsic versus intrinsic goal framing and internally controlling versus autonomy-supportive communication style upon early adolescents academic achievement”, Child Development, Vol. 76 No. 2, pp. 483–501. http://doi.org/10.1111/j.1467-8624.2005.00858.xGoogle Scholar
Venkatesh, V. and Davis, F.D. (2000), “A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies”, Management Science, Vol. 46 No. 2, pp. 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926Google Scholar
Vlassenroot, S., Brookhuis, K., Marchau, V. and Witlox, F. (2010), “Towards defining a unified concept for the acceptability of Intelligent Transport Systems (ITS): A conceptual analysis based on the case of Intelligent Speed Adaptation (ISA)”, Transportation Research Part F: Traffic Psychology and Behaviour, Vol. 13 No. 3, pp. 164–178. http://doi.org/10.1016/j.trf.2010.02.001Google Scholar
Watkins Allen, M., Walker, K.L., Coopman, S.J. and Hart, J.L. (2007), “Workplace surveillance and privacy”, Management Communication Quarterly, Vol. 21 No. 2, pp. 172–200. http://doi.org/10.1177/0893318907306033Google Scholar
Wickens, C.D. (2017), “Mental workload: assessment, prediction and consequences”, in Longo, L. and Leva, M.C. (Eds.), Human Mental Workload: Models and Applications: First International Symposium, H-WORKLOAD 2017, Dublin, Ireland, June 28-30, 2017, Revised Selected Papers, Springer International Publishing, Cham, pp. 18–29.Google Scholar
Young, M., Brookhuis, K., Wickens, C. and Hancock, P. (2014), “State of science: Mental workload in ergonomics”, Ergonomics, Vol. 58 No. 1, pp. 1–17. http://doi.org/10.1080/00140139.2014.956151Google Scholar