Organizational Readiness in Industry 4.0: Mapping the Missing Link between Technology, Human Factors, and Digital Transformation

Authors

  • Rizal Ardianto Insan Cendekia Mandiri Institute of Technology, Sidoarjo, East Java - Indonesia
  • Danny Dwi Rachmanto Insan Cendekia Mandiri Institute of Technology, Sidoarjo, East Java - Indonesia
  • Feni Ira Puspita Insan Cendekia Mandiri Institute of Technology, Sidoarjo, East Java - Indonesia
  • Adinda Sukma Novelia Insan Cendekia Mandiri Institute of Technology, Sidoarjo, East Java - Indonesia
  • Siti Fatimah Insan Cendekia Mandiri Institute of Technology, Sidoarjo, East Java - Indonesia
  • Bamban Handriyanto Master of Industrial Engineering, Faculty of Industrial Technology, Adhi Tama Institute of Technology Surabaya, Jl. Arief Rahman Hakim No. 100, Klampis Ngasem, Sukolilo District, Surabaya, East Java, 60117 - Indonesia

Keywords:

Digital twins, human factors, manufacturing, readiness

Abstract

This study aims to map the research landscape of digital transformation and Industry 4.0 through a multidisciplinary approach. A Systematic Literature Review (SLR) was conducted on 21 articles published between 2022 and 2023, obtained through a filtered search on ScienceDirect. The bibliometric analysis indicates that Industry 4.0 represents the dominant cluster with the highest frequency (20 occurrences), followed by digital transformation (6 occurrences) and digitalization (5 occurrences). Central concepts such as digital twin, sustainability, manufacturing, and supply chain also show significant PageRank values, including manufacturing (1,193,667), digitalization (1,017,000), and Industry 4.0 (889,500). However, the correspondence analysis highlights a thematic distance from human factors and organizational readiness, with keywords such as digital readiness (-4.24, -0.36) and employee’s perspective being less integrated into the mainstream discourse. These findings suggest that research on digital transformation in manufacturing remains polarized between the digitalization of core processes (e.g., manufacturing, supply chain, automation) and the development of new conceptual frameworks (e.g., organizational readiness, digital maturity, and the biologization of manufacturing). The main contribution of this study lies in identifying the integration gap between technology, human factors, and organizational readiness in the context of Industry 4.0, thereby offering directions for future research to expand the focus toward strategic dimensions, sustainability, and digital business model innovation.

References

Abouzid, I., & Saidi, R. (2023). Digital twin implementation approach in supply chain processes. Scientific African, 21(March), e01821. https://doi.org/10.1016/j.sciaf.2023.e01821

Chari, A., Stahre, J., Bärring, M., Despeisse, M., Li, D., Friis, M., Mörstam, M., & Johansson, B. (2023). Analyzing the antecedents to digital platform implementation for resilient and sustainable manufacturing supply chains - An IDEF0 modeling approach. Journal of Cleaner Production, 429(August). https://doi.org/10.1016/j.jclepro.2023.139598

Chari, A., Stahre, J., Maja, B., Li, D., & Friis, M. (2023). Analyzing the antecedents to digital platform implementation for resilient and sustainable manufacturing supply chains - An IDEF0 modeling approach Arpita. 429(November). https://doi.org/10.1016/j.jclepro.2023.139598

Clausen, P. (2023). Towards the Industry 4.0 agenda: Practitioners' reasons why a digital transition of shop floor management visualization boards is warranted. Digital Business, 3(2), 100063. https://doi.org/10.1016/j.digbus.2023.100063

Davila, M. F. R., Schwark, F., Dawel, L., & Pehlken, A. (2023). Sustainability Digital Twin: a tool for the manufacturing industry. Procedia CIRP, 116, 143–148. https://doi.org/10.1016/j.procir.2023.02.025

Gaglio, C., Kraemer-Mbula, E., & Lorenz, E. (2022). The effects of digital transformation on innovation and productivity: Firm-level evidence from South African manufacturing micro and small enterprises. Technological Forecasting and Social Change, 182(March), 121785. https://doi.org/10.1016/j.techfore.2022.121785

González Chávez, C.A., Unamuno, G., Despeisse, M., Johansson, B., Romero, D., & Stahre, J. (2023). Analyzing the risks of digital servitization in the machine tool industry. Robotics and Computer-Integrated Manufacturing, 82(August 2022). https://doi.org/10.1016/j.rcim.2022.102520

Hajoary, P. K. (2022). Industry 4.0 Maturity and Readiness- A case of a Steel Manufacturing Organization. Procedia Computer Science, 217(2022), 614–619. https://doi.org/10.1016/j.procs.2022.12.257

Holmström, J. (2022). From AI to digital transformation: The AI readiness framework. Business Horizons, 65(3), 329–339. https://doi.org/10.1016/j.bushor.2021.03.006

Holopainen, M., Ukko, J., & Saunila, M. (2022). Managing the strategic readiness of industrial companies for digital operations. Digital Business, 2(2), 100039. https://doi.org/10.1016/j.digbus.2022.100039

Kryukov, V., Shakhgeldyan, K., Kiykova, E., Kiykova, D., & Saychuk, D. (2022). Assessment of transport enterprise readiness for digital transformation. Transportation Research Procedia, 63, 2710–2718. https://doi.org/10.1016/j.trpro.2022.06.313

Musyarofah, SA, Tontowi, AE, Masruroh, NA, & Wibowo, BS (2023). Developing supply chain readiness measurement tool for the manufacturing industrial estates. Journal of Open Innovation: Technology, Markets, and Complexity, 9(1), 100019. https://doi.org/10.1016/j.joitmc.2023.100019

P. Senna, P., Barros, A.C., Bonnin Roca, J., & Azevedo, A. (2023). Development of a digital maturity model for Industry 4.0 based on the technology-organization-environment framework. Computers and Industrial Engineering, 185(September). https://doi.org/10.1016/j.cie.2023.109645

Panagiotopoulou, V. C., & Stavropoulos, P. (2023). Developing a methodology for integrating Digital Tools in Biological Manufacturing. Procedia CIRP, 118, 993–997. https://doi.org/10.1016/j.procir.2023.06.194

Piccialli, F., Chiaro, D., Sarwar, S., Cerciello, D., Qi, P., & Mele, V. (2025). AgentAI: A comprehensive survey on autonomous agents in distributed AI for industry 4.0. Expert Systems with Applications, 291(May), 128404. https://doi.org/10.1016/j.eswa.2025.128404

Rais, M.H., Ahsan, M., & Ahmed, I. (2023). FRoMEPP: Digital forensic readiness framework for material extrusion based 3D printing process. Forensic Science International: Digital Investigation, 44, 301510. https://doi.org/10.1016/j.fsidi.2023.301510

Riquelme-Medina, M., Stevenson, M., Barrales-Molina, V., & Llorens-Montes, F.J. (2022). Coopetition in business Ecosystems: The key role of absorptive capacity and supply chain agility. Journal of Business Research, 146(November 2021), 464–476. https://doi.org/10.1016/j.jbusres.2022.03.071

Rodríguez-Espíndola, O., Chowdhury, S., Dey, P.K., Albores, P., & Emrouznejad, A. (2022). Analysis of the adoption of emergent technologies for risk management in the era of digital manufacturing. Technological Forecasting and Social Change, 178(February 2021), 121562. https://doi.org/10.1016/j.techfore.2022.121562

Seegrün, A., Kruschke, T., Mügge, J., Hardinghaus, L., Knauf, T., Riedelsheimer, T., & Lindow, K. (2023). Sustainable product lifecycle management with Digital Twins: A systematic literature review. Procedia CIRP, 119, 776–781. https://doi.org/10.1016/j.procir.2023.03.124

Silva, R.P., Saraiva, C., & Mamede, H.S. (2022). Assessment of organizational readiness for digital transformation in SMEs. Procedia Computer Science, 204(2021), 362–369. https://doi.org/10.1016/j.procs.2022.08.044

Soleymanizadeh, H., Qu, Q., Bamakan, S.M.H., & Zanjirchi, S.M. (2023). Digital Twin Empowering Manufacturing Paradigms: Lean, Agile, Just-in-Time (Jit), Flexible, Resilience, Sustainable. Procedia Computer Science, 221, 1258–1267. https://doi.org/10.1016/j.procs.2023.08.114

Tabares, S., Parida, V., & Visnjic, I. (2023). Revenue models for digital services in the railway industry: A framework for choosing the right revenue model. Journal of Business Research, 165(May), 114041. https://doi.org/10.1016/j.jbusres.2023.114041

Tanveer, U., Kremantzis, M.D., Roussinos, N., Ishaq, S., Kyrgiakos, L.S., & Vlontzos, G. (2023). A fuzzy TOPSIS model for selecting digital technologies in circular supply chains. Supply Chain Analytics, 4(September), 100038. https://doi.org/10.1016/j.sca.2023.100038

Tomelleri, F., Sbaragli, A., Picariello, F., & Pilati, F. (2024). Digital ergonomic assessment to enhance the physical resilience of human-centric manufacturing systems in Industry 5.0. Journal of Manufacturing Systems, 77, 246–265. https://doi.org/10.1016/j.jmsy.2024.09.003

Trabert, T., Beiner, S., Lehmann, C., & Kinkel, S. (2022). Digital Value Creation in Sociotechnical Systems. Procedia Computer Science, 200(2019), 471–481. https://doi.org/10.1016/j.procs.2022.01.245

Visual Digital Readiness

Downloads

Published

2025-07-31

How to Cite

Ardianto, R., Rachmanto, D. D., Puspita, F. I., Novelia, A. S., Fatimah, S., & Handriyanto, B. (2025). Organizational Readiness in Industry 4.0: Mapping the Missing Link between Technology, Human Factors, and Digital Transformation. Journal of Smart Lean Manufacturing and Process Enhancement, 1(1), 41–53. Retrieved from https://jurnal.unikchers.com/jslmpe/article/view/34

Issue

Section

Articles