Evaluation of conventional and industry 4.0 manufacturing work design factors for performance based on personal characteristics
Abstract
Performance of workers can be improved by effective design of work. Several work design factors, physiological, psychological, technological, organizational and social, have been identified in research literature. These factors influence the work in different forms, especially in combination with personal characteristics of workers. Manufacturing technologies are also changing with adoption of industry 4.0 practices. The objective of the research was to test whether workers with different personal characteristics had different relationships with work design factors in the conventional setting. The findings for the current conventional setup are extrapolated on an industry 4.0 work design model with important insights and observations. Managerial implications were inferred from the results which indicated age, education and family size as important variables affecting supervision (Mean HSE ( , training ( ), aptitude ( , pay and welfare ( ), job rotation , feedback , pace of operations , in conventional manufacturing. Old, experienced, educated and married workers with children give certain initiatives to management, which should be utilized for better performance in industry 4.0 production work.
Keywords: Human Resource, industry 4.0, personal characteristics, production worker, work design
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Alharbi, M. F., Alahmadi, B. A., Alali, M., & Alsaedi, S. (2019). Quality of nursing work life among hospital nurses in Saudi Arabia: A cross‐sectional study. Journal of Nursing Management, 27(8), 1722-1730.
Altmann, N., Kohler, C., & Meil, P. (2017). Technology and work in German industry (Vol. 1). Taylor & Francis.
Bakker, A. B., & Albrecht, S. (2018). Work engagement: current trends. Career Development International.
Basha, S. A., & Maiti, J. (2017). Assessment of work compatibility across employees’ demographics: a case study. International journal of injury control and safety promotion, 24(1), 106-119.
Bødker, S. (2016). Rethinking technology on the boundaries of life and work. Personal and Ubiquitous Computing, 20(4), 533-544.
Bugvia, S. A., Hameeda, K., Hussain, A., & Tabassum, S. A. (2021). The CPEC supply web framework in context of modern manufacturing. Jurnal Kejuruteraan, 33(1), 39-46.
Bugvi, S. A., Hameed, K. Jamil, F. Irfan, A. Murtaza, S. Qaisar, M. & Bilal, M. (2021). performance improvement through Value Stream Mapping – A manufacturing case study. Jurnal Kejuruteraan, 33(4), 1007-1018.
Cassar, L., & Meier, S. (2018). Nonmonetary incentives and the implications of work as a source of meaning. Journal of Economic Perspectives, 32(3), 215-38.
Chavaillaz, A., Schwaninger, A., Michel, S., & Sauer, J. (2019). Work design for airport security officers: Effects of rest break schedules and adaptable automation. Applied Ergonomics, 79, 66-75.
Das, B. (1999). Development of a comprehensive industrial work design model. Human Factors and Ergonomics in Manufacturing & Service Industries, 9(4), 393-411.
Davis, M. M., Aquilano, N. J., Balakrishnan, J. & Chase, R. B. (2005). Fundamentals of operations management. McGraw-Hill Ryerson.
Dawal, S. Z., Taha, Z., & Ismail, Z. (2009). Effect of job organization on job satisfaction among shop floor employees in automotive industries in Malaysia. International Journal of Industrial Ergonomics, 39(1), 1-6.
Duarte, S., & Cruz-Machado, V. (2017, July). Exploring linkages between lean and green supply chain and the industry 4.0. In International conference on management science and engineering management (pp. 1242-1252). Springer, Cham.
Fantini, P., Pinzone, M., & Taisch, M. (2020). Placing the operator at the centre of Industry 4.0 design: Modelling and assessing human activities within cyber-physical systems. Computers & Industrial Engineering, 139, 105058.
Field, A. P., & Miles, J. (2009). Discovering statistics using SPSS:(and sex and drugs and rock'n'roll). Sage.
Field, A. (2013). Discovering statistics using IBM SPSS statistics. Sage.
Fletcher, S. R., Baines, T. S., & Harrison, D. K. (2008). An investigation of production workers’ performance variations and the potential impact of attitudes. The International Journal of Advanced Manufacturing Technology, 35(11), 1113-1123.
Hamid, R. A., Rahid, M. R., & Ab Hamid, S. N. (2020). The effects of employee participation in creative-relevant process and creative self-efficacy on employee creativity. Geografia-Malaysian Journal of Society and Space, 16(2), 179-191.
Hommelhoff, S., Schröder, C., & Niessen, C. (2020). The experience of personal growth in different career stages: An exploratory study. Organisationsberatung, Supervision, Coaching, 27(1), 5-19.
Kadir, B. A., Broberg, O., da Conceição Carolina, S., & Jensen, N. G. (2019). A framework for designing work systems in industry 4.0. In Proceedings of the Design Society: International Conference on Engineering Design (Vol. 1, No. 1, pp. 2031-2040). Cambridge University Press.
Linz, S. J. (2004). Motivating Russian workers: Analysis of age and gender differences. The Journal of Socio-Economics, 33(3), 261-289.
Malik, A. (2018). Strategic human resource management and employment relations. Springer Nature Singapore Pte Ltd.
Mital, A., & Pennathur, A. (2004). Advanced technologies and humans in manufacturing workplaces: An interdependent relationship. International journal of industrial ergonomics, 33(4), 295-313.
Parker, S. K. (2017). Work design growth model: How work characteristics promote learning and development. In J. E. Ellingson & R. A. Noe (Eds.), Autonomous learning in the workplace (pp. 137–161). Routledge/Taylor & Francis Group. https://doi.org/10.4324/ 9781315674131-8
Parker, S. K., Morgeson, F. P., & Johns, G. (2017). One hundred years of work design research: Looking back and looking forward. Journal of applied psychology, 102(3), 403.
Parker, S. K., Van den Broeck, A., & Holman, D. (2017). Work design influences: A synthesis of multilevel factors that affect the design of jobs. Academy of Management Annals, 11(1), 267-308.
Paruzel, A., Bentler, D., Schlicher, K. D., Nettelstroth, W., & Maier, G. W. (2019). Employees first, technology second. Zeitschrift für Arbeits-und Organisationspsychologie A&O.
Rahman, M. R. C. A., Ibrahim, I. A., & Madinah, D. (2020). Are highly unionised industries socially responsible to their employees?. Geografia-Malaysian Journal of Society and Space, 16(2), 215-227.
Sauter, S. L., Brightwell, W. S., Colligan, M. J., Hurrell, J. J., & Katz, T. M. (2002). Changing organization of work and the safety and health of working people. Cincinnati: National Institute for Occupational Safety and Health.
Seixas, A., Ferreira, T., Silva, M. V., & Rodrigues, M. A. (2018). The impact of shift work on burnout syndrome, depression, anxiety and stress: A case study in the metalworking industry. International Journal of Occupational and Environmental Safety, 2(1), 1-8.
Shantz, A., Alfes, K., Truss, C., & Soane, E. (2013). The role of employee engagement in the relationship between job design and task performance, citizenship and deviant behaviours. The International Journal of Human Resource Management, 24(13), 2608-2627.
Taghavi, A., & Woo, C. (2017). The role clarity framework to improve requirements gathering. ACM Transactions on Management Information Systems (TMIS), 8(2-3), 1-16.
Taylor, F. W., (1911). The principles of scientific management. New York, 202.
Thatcher, A. (2013). Green ergonomics: definition and scope. Ergonomics, 56(3), 389-398.
Torraco, R. J. (2005). Work design theory: A review and critique with implications for human resource development. Human resource development quarterly, 16(1), 85-109.
Velada, R., Caetano, A., Michel, J. W., Lyons, B. D., & Kavanagh, M. J. (2007). The effects of training design, individual characteristics and work environment on transfer of training. International journal of training and development, 11(4), 282-294.
Warr, T. D., Corbett, J. M., Clegg, C. W., Jackson, P. R., & Martin, R. (1990). Advanced manufacturing technology and work design: Towards a theoretical framework. Journal of Organizational Behavior, 11(3), 201-219.
Warr, P., Schaie, K. & Schooler, C. (1998). Impact of work on older adults. New York: Springer.
Waschull, S., Bokhorst, J. A., & Wortmann, J. C. (2017). Impact of technology on work: Technical functionalities that give rise to new job designs in industry 4.0. In IFIP International Conference on Advances in Production Management Systems (pp. 274-281). Springer, Cham.
Waschull, S., Bokhorst, J. A., Molleman, E., & Wortmann, J. C. (2020). Work design in future industrial production: Transforming towards cyber-physical systems. Computers & industrial engineering, 139, 105679.
Wolf, M., Kleindienst, M., Ramsauer, C., Zierler, C., & Winter, E. (2018). Current and future industrial challenges: demographic change and measures for elderly workers in industry 4.0. Annals of the Faculty of Engineering Hunedoara, 16(1), 67-76.
Zacher, H., & Schmitt, A. (2016). Work characteristics and occupational well-being: the role of age. Frontiers in psychology, 7, 1411.
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