Production
https://prod.org.br/article/doi/10.1590/0103-6513.20240109
Production
Thematic Section - Industry 5.0: Human-centric production management (Social systems for future manufacturing)

Human-centric process improvement through digital transformation: contributions and limitations

Camilla Buttura Chrusciak; Anderson Luis Szejka; Osiris Canciglieri Junior; Jones Luís Schaefer

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Abstract

Paper aims: This study investigates integrating digital transformation, human factors, business process management, and emerging technologies to improve organisational efficiency and employee well-being. The research aims to develop a conceptual model that optimises digital processes while reducing the cognitive load on employees.

Originality: The research fills a gap in the literature by emphasising the intersection of human factors and digital transformation. It introduces a human-centric approach that balances operational efficiency with employee well-being, which has been underexplored in previous studies.

Research method: A systematic literature review was conducted using Scopus and Web of Science databases to identify relevant studies. Content analysis was used to extract criteria for each domain, and Structural Equation Modelling (SEM) was applied to analyse complex relationships between digital transformation and human factors.

Main findings: The results indicate that integrating digital tools into organisational processes optimises workflows and decision-making while mitigating cognitive overload. The proposed model prioritises employee engagement, usability, and well-being alongside technological advancement.

Implications for theory and practice: This study contributes to the theoretical understanding of digital transformation by integrating human factors. The findings provide a structured pathway for organisations to enhance operational efficiency while safeguarding employee well-being, offering a balanced approach to digitalisation that can be applied in real-world scenarios.

Keywords

Digital transformation, Business process management, Human factors, Structural equation modelling

References

Autor, D. H. (2015). Why are there still so many jobs? The history and future of workplace automation. The Journal of Economic Perspectives, 29(3), 3-30. http://doi.org/10.1257/jep.29.3.3.

Bellantuono, N., Nuzzi, A., Pontrandolfo, P., & Scozzi, B. (2021). Digital transformation models for the I4.0 transition: lessons from the change management literature. Sustainability, 13(23), 12941. http://doi.org/10.3390/su132312941.

Butt, J. (2020). A conceptual framework to support digital transformation in manufacturing using an integrated business process management approach. Designs, 4(3), 17. http://doi.org/10.3390/designs4030017.

Demerouti, E., Bakker, A. B., & Halbesleben, J. R. B. (2019). Accelerated change and stress: A longitudinal test of the job demands-resources model in the context of organisational change. Journal of Occupational Health Psychology, 24(1), 25-37. http://doi.org/10.1037/ocp0000106.

Duarte, A. L. F., Vieira, P. R. C., & Silva, A. C. M. (2016). Dimensões que impactam a satisfação do usuário de sistema de informação acadêmica: estudo com emprego de modelagem de equações estruturais com base em mínimos quadrados parciais. Exacta, 14(1), 139-148. http://doi.org/10.5585/exactaep.v14n1.5963.

Golan, M., Cohen, Y., & Singer, G. (2020). A framework for operator: workstation interaction in Industry 4.0. International Journal of Production Research, 58(8), 2421-2432. http://doi.org/10.1080/00207543.2019.1639842.

Grácio, M. C. C., & Oliveira, E. F. T. (2012). Visibilidade dos pesquisadores no periódico Scientometrics a partir da perspectiva brasileira: um estudo de cocitação. Em Questão, 18(esp), 99-113. http://doi.org/10.19132/1808-5245243-113.

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). Los Angeles: SAGE.

Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial least squares structural equation modelling (PLS-SEM) using R: a workbook. Cham: Springer. http://doi.org/10.1007/978-3-030-80519-7

Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: indeed, a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139-151. http://doi.org/10.2753/MTP1069-6679190202.

Heberle, A., Lowe, W., Gustafsson, A., & Vorrei, O. (2017). Digitalisation canvas: towards identifying digitalisation use cases and projects. Computers in Industry, 90, 1070-1097. http://doi.org/10.1016/j.compind.2017.07.001.

Hermann, M., Bücker, I., & Otto, B. (2019). Industrie 4.0 process transformation: Findings from a case study in automotive logistics. Journal of Manufacturing Technology Management, 31(5), 935-953. http://doi.org/10.1108/JMTM-08-2018-0274.

Hoch, N. B., & Brad, S. (2020). Managing business model innovation: An innovative approach towards designing a digital ecosystem and multi-sided platform. Business Process Management Journal, 27(2), 415-438. http://doi.org/10.1108/BPMJ-01-2020-0017.

Kadir, B. A., & Broberg, O. (2021). Human-centered design of work systems in the transition to industry 4.0. Applied Ergonomics, 92, 103334. http://doi.org/10.1016/j.apergo.2020.103334. PMid:33264676.

Liu, Y., Ni, Z., Karlsson, M., & Gong, S. (2021). Methodology for digital transformation with Internet of Things and cloud computing: a practical guideline for innovation in small- and medium-sized enterprises. Sensors, 21(16), 5355. http://doi.org/10.3390/s21165355. PMid:34450797.

Margiono, A. (2021). Digital transformation: setting the pace. The Journal of Business Strategy, 42(5), 315-322. http://doi.org/10.1108/JBS-11-2019-0215.

Martinez, F. (2019). Process excellence: the key for digitalisation. Business Process Management Journal, 25(7), 1716-1733. http://doi.org/10.1108/BPMJ-08-2018-0237.

Moencks, M., Roth, E., Bohné, T., Romero, D., & Stahre, J. (2022). Augmented workforce canvas: a management tool for guiding human-centric, value-driven human-technology integration in industry. Computers & Industrial Engineering, 163, 107910. http://doi.org/10.1016/j.cie.2021.107803.

Neumann, W. P., Winkelhaus, S., Grosse, E. H., & Glock, C. H. (2021). Industry 4.0 and the human factor: a systems framework and analysis methodology for successful development. International Journal of Production Economics, 233, 107973. http://doi.org/10.1016/j.ijpe.2020.107992.

Organization for Economic Co-Operation and Development – OECD. (2019). The future of work: OECD employment outlook 2019. Paris: OECD Publishing. http://doi.org/10.1787/9ee00155-en.

Papetti, A., Pandolfi, M., Peruzzini, M., & Germani, M. (2020). A framework to promote social sustainability in Industry 4.0. International Journal of Agile Systems and Management, 13(3), 233-257. http://doi.org/10.1504/IJASM.2020.109243.

Parida, V., Sjödin, D., & Reim, W. (2019). Reviewing literature on digitalisation, business model innovation, and sustainable industry: past achievements and future promises. Sustainability, 11(2), 391. http://doi.org/10.3390/su11020391.

Perez, H. D., Wassick, J. M., & Grossmann, I. E. (2022). A digital twin framework for online optimisation of supply chain business processes. Computers & Chemical Engineering, 159, 107599.

Ribeiro, V. B., Nakano, D., & Muniz Junior, J. (2024). The human resources and knowledge management integrated role in Industry 4.0/5.0: a human-centric operations management framework. Production, 34, e20240014. http://doi.org/10.1590/0103-6513.20240014.

Richard, S., Pellerin, R., Bellemare, J., & Perrier, N. (2020). A business process and portfolio management approach for Industry 4.0 transformation. Business Process Management Journal, 27(2), 505-528. http://doi.org/10.1108/BPMJ-05-2020-0216.

Richter, A., Riemer, K., & vom Brocke, J. (2016). The impact of technostress on productivity: a systematic literature review. Information Systems Journal, 26(1), 35-76.

Sengers, F., Wieczorek, A. J., & Raven, R. (2016). Experimenting for sustainability transitions: a systematic literature review. Technological Forecasting and Social Change, 104, 289-300.

Stapel, J., Mullakkal-Babu, F. A., & Happee, R. (2019). Automated driving reduces perceived workload, but monitoring causes a higher cognitive load than manual driving. Transportation Research Part F: Traffic Psychology and Behaviour, 60, 590-605. http://doi.org/10.1016/j.trf.2018.11.006.

Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a methodology for developing evidence-informed management knowledge by means of systematic review. British Journal of Management, 14(1), 207-222. http://doi.org/10.1111/1467-8551.00375.

Vial, G. (2019). Understanding digital transformation: a review and a research agenda. The Journal of Strategic Information Systems, 28(2), 118-144. http://doi.org/10.1016/j.jsis.2019.01.003.

Westerman, G., Bonnet, D., & McAfee, A. (2014). Leading digital: turning technology into business transformation. Boston: Harvard Business Press.

Yoshikawa, N. K., Costa Filho, J. R., Penha, R., Kniess, C. T., & Souza, J. D. (2020). Agile approach as a strategy in digital transformation projects: a bibliometric review and bibliographic study. International Journal of Professional Business Review, 5(2), 272-287. http://doi.org/10.26668/businessreview/2020.v5i2.218.
 


Submitted date:
10/28/2024

Accepted date:
02/18/2025

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