DOI: https://doi.org/10.14710/jati.20.3.220-225

ADAPTIVE PRODUCTIVITY MODEL: INTEGRATING LEAN OFFICE AND INDUSTRY 4.0 IN MODERN ADMINISTRATIVE SYSTEMS

Anjeli Riza Umami  -  Universitas PGRI Adi Buana Surabaya, Indonesia
*Muhamad Abdul Jumali orcid scopus publons  -  Universitas PGRI Adi Buana Surabaya, Indonesia
Rusdiyantoro Rusdiyantoro  -  Universitas PGRI Adi Buana Surabaya, Indonesia

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Abstract

In the wake of digital disruption and operational volatility, organizations are compelled to reimagine productivity beyond traditional efficiency. This study introduces an adaptive productivity model by fusing Lean Office practices with Industry 4.0 technologies—specifically IoT, AI, and Big Data analytics—within administrative systems of professional service firms. Using a mixed-methods design, data from 44 participants in a public valuation office were analyzed through multiple regression, revealing a strong predictive capacity (R² = 0.908). Lean Office (β = 0.281, p = 0.016) and Industry 4.0 (β = 0.253, p = 0.020) both demonstrated significant contributions to enhanced productivity and operational responsiveness. Over 93% of respondents observed reduced process time, while 98% acknowledged improved cross-functional collaboration. These results confirm that digital-lean convergence fosters an agile, sustainable, and data-informed working culture. The proposed model offers a future-ready framework for administrative transformation—one that is lean by design, smart by technology, and resilient by culture.

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Keywords: Adaptive Productivity; Lean Office; Industry 4.0; Administrative Efficiency; Smart Office; Digital Transformation

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Section: Research Articles
Language : EN
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  1. ABDULLAHI, U. (n.d.). THE ANTECEDENTS OF ORGANIZATIONAL RESILIENCE: TOWARDS IMPROVING THE SUSTAINABILITY OF PUBLIC SECTOR ORGANIZATIONS IN NIGERIA
  2. AlManei, M., Salonitis, K., & Tsinopoulos, C. (2018). A conceptual lean implementation framework based on change management theory. Procedia CIRP, 72, 1160–1165. https://doi.org/https://doi.org/10.1016/j.procir.2018.03.141
  3. Bahia, T. H. A., Idan, A. R., & Athab, K. R. (2023). The Effect of Quality Function Deployment (Qfd) in Enhancing Customer Satisfaction. International Journal of Professional Business Review, 8(1), 18. https://doi.org/10.26668/businessreview/2023.v8i1.1156
  4. Braun, V., & Clarke, V. (2021). To saturate or not to saturate? Questioning data saturation as a useful concept for thematic analysis and sample-size rationales. Qualitative Research in Sport, Exercise and Health, 13(2), 201–216
  5. Buer, S.-V., Strandhagen, J. O., & Chan, F. (2018). The link between Industry 4.0 and lean manufacturing: mapping current research and establishing a research agenda. International Journal of Production Research, 56, 1–17. https://doi.org/10.1080/00207543.2018.1442945
  6. Clark, L. A., & Watson, D. (2019). Constructing validity: New developments in creating objective measuring instruments. Psychological Assessment, 31(12), 1412
  7. Costa, F., Frecassetti, S., Rossini, M., & Portioli-Staudacher, A. (2023). Industry 4.0 digital technologies enhancing sustainability: Applications and barriers from the agricultural industry in an emerging economy. Journal of Cleaner Production, 408, 137208
  8. Dalenogare, L. S., Benitez, G. B., Ayala, N. F., & Frank, A. G. (2018). The expected contribution of Industry 4.0 technologies for industrial performance. International Journal of Production Economics, 204, 383–394. https://doi.org/https://doi.org/10.1016/j.ijpe.2018.08.019
  9. Dombrowski, U., & Mielke, T. (2013). Lean Leadership – Fundamental Principles and their Application. Procedia CIRP, 7, 569–574. https://doi.org/https://doi.org/10.1016/j.procir.2013.06.034
  10. Frank, A. G., Dalenogare, L. S., & Ayala, N. F. (2019). Industry 4.0 technologies: Implementation patterns in manufacturing companies. International Journal of Production Economics, 210, 15–26. https://doi.org/https://doi.org/10.1016/j.ijpe.2019.01.004
  11. Frank, A. G., Mendes, G. H. S., Ayala, N. F., & Ghezzi, A. (2019). Servitization and Industry 4.0 convergence in the digital transformation of product firms: A business model innovation perspective. Technological Forecasting and Social Change, 141, 341–351
  12. Ghobakhloo, M. (2020). Industry 4.0, digitization, and opportunities for sustainability. Journal of Cleaner Production, 252, 119869. https://doi.org/https://doi.org/10.1016/j.jclepro.2019.119869
  13. Gupta, S., Sharma, M., & M., V. S. (2016). Lean services: a systematic review. International Journal of Productivity and Performance Management, 65(8), 1025–1056. https://doi.org/10.1108/IJPPM-02-2015-0032
  14. Hair, J. F. (2021). Reflections on SEM: An introspective, idiosyncratic journey to composite-based structural equation modeling. ACM SIGMIS Database: The DATABASE for Advances in Information Systems, 52(SI), 101–113
  15. Heeres, T. J., Tran, T. M., & Noort, B. A. C. (2023). Drivers and barriers to implementing the internet of things in the health care supply chain: mixed methods multicase study. Journal of Medical Internet Research, 25, e48730
  16. Hicks, B. J. (2007). Lean information management: Understanding and eliminating waste. International Journal of Information Management, 27(4), 233–249. https://doi.org/https://doi.org/10.1016/j.ijinfomgt.2006.12.001
  17. Kamble, S., Gunasekaran, A., & Dhone, N. C. (2020). Industry 4.0 and lean manufacturing practices for sustainable organisational performance in Indian manufacturing companies. International Journal of Production Research, 58(5), 1319–1337
  18. Kendall, H., Clark, B., Li, W., Jin, S., Jones, G. D., Chen, J., Taylor, J., Li, Z., & Frewer, L. J. (2022). Precision agriculture technology adoption: A qualitative study of small-scale commercial “family farms” located in the North China Plain. Precision Agriculture, 1–33
  19. Komkowski, T., Michael, S., Jiju, A., Fabiane Letícia, L., Jose Arturo, G.-R., & and Tortorella, G. L. (2025). Operational practices for integrating lean and industry 4.0 – a dynamic capabilities perspective. International Journal of Production Research, 63(4), 1517–1537. https://doi.org/10.1080/00207543.2024.2381127
  20. Lang, L. D., Tiwari, A. K., Hieu, H. N., Ha, N. M., & Gaur, J. (2023). The role of structural social capital in driving social-oriented sustainable agricultural entrepreneurship. Energy Economics, 124, 106855. https://doi.org/https://doi.org/10.1016/j.eneco.2023.106855
  21. Luthra, S., & Mangla, S. K. (2018). Evaluating challenges to Industry 4.0 initiatives for supply chain sustainability in emerging economies. Process Safety and Environmental Protection, 117, 168–179. https://doi.org/https://doi.org/10.1016/j.psep.2018.04.018
  22. Meeker, W. Q., Escobar, L. A., & Pascual, F. G. (2022). Statistical methods for reliability data. John Wiley & Sons
  23. Milazzo, P., Sgandurra, M., Matarazzo, A., Grassia, L., & Bertino, A. (2017). The new ISO 14001: 2015 standard as a strategic application of life cycle thinking. Procedia Environmental Science, Engineering and Management, 4(2), 119–126
  24. Moeuf, A., Pellerin, R., Lamouri, S., Tamayo Giraldo, S., & Barbaray, R. (2017). The industrial management of SMEs in the era of Industry 4.0. International Journal of Production Research, 56, 1–19. https://doi.org/10.1080/00207543.2017.1372647
  25. Mohan Modak, N., Senapati, T., Simic, V., Pamucar, D., Saha, A., & Cárdenas-Barrón, L. E. (2024). Managing a sustainable dual-channel supply chain for fresh agricultural products using blockchain technology. Expert Systems with Applications, 244, 122929. https://doi.org/https://doi.org/10.1016/j.eswa.2023.122929
  26. Mundra, N., Mishra, R. P., & Upreti, G. (2021). Development of framework for lean implementation. SAE International Journal of Materials and Manufacturing, 14(2), 223–242
  27. Patankar, N., Fell, H. G., Rodrigo de Queiroz, A., Curtis, J., & DeCarolis, J. F. (2022). Improving the representation of energy efficiency in an energy system optimization model. Applied Energy, 306, 118083. https://doi.org/https://doi.org/10.1016/j.apenergy.2021.118083
  28. Pereira, A. C., Alves, A. C., & Arezes, P. (2023). Augmented reality in a lean workplace at smart factories: a case study. Applied Sciences, 13(16), 9120
  29. Porter, M. E., & Heppelmann, J. E. (2025). How smart, connected products are transforming companies. https://www.bollettinoadapt.it/wp-content/uploads/2015/09/How-Smart-Connected-Products-Are-Transforming-Companies.pdf
  30. Qalati, S. A., Zafar, Z., Fan, M., Sánchez Limón, M. L., & Khaskheli, M. B. (2022). Employee performance under transformational leadership and organizational citizenship behavior: A mediated model. Heliyon, 8(11), e11374. https://doi.org/https://doi.org/10.1016/j.heliyon.2022.e11374
  31. Slater, S. F. (1996). The challenge of sustaining competitive advantage. Industrial Marketing Management, 25(1), 79–86
  32. Sossa, J. W. Z., Posada, N. G., Montoya, L. H. B., Monsalve, A. M. Z., Piedrahíta, J. C. P., Mendoza, G. L. O., Grisales, L. V., & Cano, L. F. G. (2024). Foresight study using scenarios and the Delphi method in the leather agroindustrial chain to 2035 - Alignment of results with open innovation. Journal of Open Innovation: Technology, Market, and Complexity, 10(3), 100374. https://doi.org/https://doi.org/10.1016/j.joitmc.2024.100374
  33. Sürücü, L., & Maslakci, A. (2020). Validity and reliability in quantitative research. Business & Management Studies: An International Journal, 8(3), 2694–2726
  34. Teichgräber, U. K., & de Bucourt, M. (2012). Applying value stream mapping techniques to eliminate non-value-added waste for the procurement of endovascular stents. European Journal of Radiology, 81(1), e47–e52. https://doi.org/https://doi.org/10.1016/j.ejrad.2010.12.045
  35. Tilley, A., Dam Lam, R., Lozano Lazo, D., Dos Reis Lopes, J., Freitas Da Costa, D., De Fátima Belo, M., Da Silva, J., Da Cruz, G., & Rossignoli, C. (2024). The impacts of digital transformation on fisheries policy and sustainability: Lessons from Timor-Leste. Environmental Science & Policy, 153, 103684. https://doi.org/https://doi.org/10.1016/j.envsci.2024.103684
  36. Womack, J., & Jones, D. (1996). Lean Thinking : Banish Waste and Create Wealth in Your Corporation. In Journal of the Operational Research Society (Vol. 48). https://doi.org/10.1038/sj.jors.2600967
  37. Yadav, V. S., Singh, A. R., Raut, R. D., Mangla, S. K., Luthra, S., & Kumar, A. (2022). Exploring the application of Industry 4.0 technologies in the agricultural food supply chain: A systematic literature review. Computers & Industrial Engineering, 169, 108304

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