Effects of Big Data, Mechanical System Flexibility, IOT and Digital Twin Adoption on Company Resilience and Operational Performance
DOI:
https://doi.org/10.31181/rme524Keywords:
Mechanical Digital Twin, Mechanical System Flexibility, IoT, Big Data Analytics Capability, Operational PerformanceAbstract
Purpose: The main purpose of this paper is to examine the effect of mechanical digital twin, mechanical system flexibility, IoT, and big data analytics on operational performance. The study also examined the mediating effect of organizational resilience in the proposed framework. Design/ method/ approach: The present research adopted a quantitative approach and survey methods to gather responses from respondents. The population of the study consisted of employees working in organizations. Convenience sampling was used for the collection of responses. A total of 202 responses were used for analysis purposes. AMOS was used for assessment of analysis. Findings: Results showed that organizational resilience has positive effect on operational performance. Moreover, IoT, Big data analytics capability, mechanical digital twin, and mechanical system flexibility have positive effect on operational performance. Findings also supported mediating effect of organizational resilience. Originality: Present study adds to the body of literature by exploring mediating role of organizational resilience.
References
Ahmed, R. (2025). Synergizing AI, IoT, and Data Science to Enhance Organizational and Urban Resilience in Unstable Economies. https://doi.org/10.22541/au.174837073.32567903/v1
Al-Mahrouqi, T., Chan, M. F., Al-Mukhaini, M., Al Shehi, M., Al-Huseini, S., Jahan, F., Al Balushi, N., Panchatcharam, S. M., & Al Alawi, M. (2023). The differential mediating roles of resilience in the relationship between meaningful living and stress among college students during the COVID-19 pandemic. Scientific reports, 13(1), 11671. https://doi.org/10.1038/s41598-023-38975-0
Amer, Y., Soufali, A., & Zaghwan, A. (2026). A digital twin-based framework for predictive quality assurance and supply chain resilience in the automotive industry. Advanced Engineering Informatics, 69, 103969. https://doi.org/10.1016/j.aei.2025.103969
Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological bulletin, 103(3), 411. https://doi.org/10.1037/0033-2909.103.3.411
Arshad, M., Qadir, A., Ahmad, W., & Rafique, M. (2024). Enhancing organizational sustainable innovation performance through organizational readiness for big data analytics. Humanities and Social Sciences Communications, 11(1), 1-15. https://doi.org/10.1057/s41599-024-03424-4
Atli, K., & Krystallis, I. (2025). Design flexibility in managing infrastructure projects: Contributing factors and research avenues. International Journal of Project Management, 43(1), 102675. https://doi.org/10.1016/j.ijproman.2025.102675
Babatunde, O. M., Munda, J. L., & Hamam, Y. (2020). Power system flexibility: A review. Energy Reports, 6, 101-106. https://doi.org/10.1016/j.egyr.2019.11.048
Babu, M. M., Rahman, M., Alam, A., & Dey, B. L. (2024). Exploring big data-driven innovation in the manufacturing sector: evidence from UK firms. Annals of Operations Research, 333(2), 689-716. https://doi.org/10.1007/s10479-021-04077-1
Bellavista, P., Giannelli, C., Mamei, M., Mendula, M., & Picone, M. (2021). Application-driven network-aware digital twin management in industrial edge environments. IEEE transactions on industrial informatics, 17(11), 7791-7801. https://doi.org/10.1109/TII.2021.3067447
Bhuiyan, M. R. I., Akter, M. S., Amin, A.-., & Hossain, R. (2025). The mediating effect of innovation capabilities, information quality and supply chain resilience in the relationship between big data analytics capability (BDAC) and healthcare performance. Sage Open, 15(3), 21582440251362262. https://doi.org/10.1177/21582440251362262
Bongomin, O., Mwape, M. C., Mpofu, N. S., Bahunde, B. K., Kidega, R., Mpungu, I. L., Tumusiime, G., Owino, C. A., Goussongtogue, Y. M., & Yemane, A. (2025). Digital Twin technology advancing Industry 4.0 and Industry 5.0 across Sectors. Results in Engineering, 105583. https://doi.org/10.1016/j.rineng.2025.105583
Buer, S.-V., Semini, M., Strandhagen, J. O., & Sgarbossa, F. (2021). The complementary effect of lean manufacturing and digitalisation on operational performance. International Journal of Production Research, 59(7), 1976-1992. https://doi.org/10.1080/00207543.2020.1790684
Capoani, L., Fantinelli, M., & Giordano, L. (2025). The concept of resilience in economics: a comprehensive analysis and systematic review of economic literature. Continuity & Resilience Review. https://doi.org/10.1108/CRR-11-2024-0045
de Souza Miguel, P. L., & Brito, L. A. L. (2011). Supply chain management measurement and its influence on operational performance. Journal of operations and supply chain management, 4(2), 56-70. https://doi.org/10.12660/joscmv4n2p56-70
Ebiloma, D. O., Aigbavboa, C. O., & Anumba, C. (2025). Key drivers of digital twin maintenance management for healthcare facilities in Nigeria. Engineering, Construction and Architectural Management, 1-20. https://doi.org/10.1108/ECAM-11-2024-1555
Fan, J.-S., Xu, M.-N., Li, Y.-C., Ding, Y.-F., Liu, Y.-F., Geng, B., & Liao, X.-J. (2025). Mechanics-based digital twin model for structural construction using 3D scanning and FE model updating. Automation in Construction, 173, 106109. https://doi.org/10.1016/j.autcon.2025.106109
Fayyaz, A., Liu, C., Xu, Y., & Ramzan, S. (2025). Effects of green human resource management, internal environmental management and developmental culture between lean six sigma and operational performance. International Journal of Lean Six Sigma, 16(1), 109-140. https://doi.org/10.1108/IJLSS-04-2023-0065
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50. https://doi.org/10.1177/002224378101800104
Garrido-Moreno, A., Martín-Rojas, R., & García-Morales, V. J. (2024). The key role of innovation and organizational resilience in improving business performance: A mixed-methods approach. International Journal of Information Management, 77, 102777. https://doi.org/10.1016/j.ijinfomgt.2024.102777
Ghomi, V., Nooraei, S. V. R., Shekarian, N., Shokoohyar, S., & Parast, M. (2023). Improving supply chain resilience through investment in flexibility and innovation. International Journal of Systems Science: Operations & Logistics, 10(1), 2221068. https://doi.org/10.1080/23302674.2023.2221068
Haddad, M. K., & Hassan, R. S. (2025). Enhancing Organizational Performance Through Agility and Resilience: A Strategic Capability Perspective. Cureus Journal of Business and Economics, 2. https://doi.org/10.7759/s44404-025-06140-7
Hair Jr, J. F., Howard, M. C., & Nitzl, C. (2020). Assessing measurement model quality in PLS-SEM using confirmatory composite analysis. Journal of Business Research, 109, 101-110. https://doi.org/10.1016/j.jbusres.2019.11.069
Hasan, S. K., & Crawford, C. W. (2025). A new era for digital twins: Progress and industry adoption. Digital Twin, 2555877. https://doi.org/10.1080/27525783.2025.2555877
Idrissi, Z. K., Lachgar, M., & Hrimech, H. (2024). Blockchain, IoT and AI in logistics and transportation: A systematic review. Transport Economics and Management, 2, 275-285. https://doi.org/10.1016/j.team.2024.09.002
Jangsiriwattana, T. (2021). The mediating effect of resilience on the relationship between perceived organizational support and work engagement. Academy of Strategic Management Journal, 20, 1-12. https://tinyurl.com/4kpjrzhr
Kantur, D., & Say, A. I. (2015). Measuring organizational resilience: A scale development. Journal of Business Economics and Finance, 4(3). https://doi.org/10.17261/Pressacademia.2015313066
Kong, T., & Feng, T. (2025). Enhancing supply chain resilience: the role of big data analytics capability and organizational ambidexterity. Industrial Management & Data Systems, 125(7), 2348-2370. https://doi.org/10.1108/IMDS-07-2024-0674
Lin, J., Wu, S., & Luo, X. (2025). How does big data analytics capability affect firm performance? Unveiling the role of organisational resilience and environmental dynamism. European Journal of Information Systems, 34(3), 502-528. https://doi.org/10.1080/0960085X.2024.2375262
Malik, P., & Garg, P. (2020). Learning organization and work engagement: The mediating role of employee resilience. The International Journal of Human Resource Management, 31(8), 1071-1094. https://doi.org/10.1080/09585192.2017.1396549
Manzini, D., Oosthuizen, R., & Chikwanda, H. K. (2025). Enhancing Organisational Resilience Through Systems Thinking. Social Sciences & Humanities Open, 12, 101783. https://doi.org/10.1016/j.ssaho.2025.101783
Maroufkhani, P., Tseng, M.-L., Iranmanesh, M., Ismail, W. K. W., & Khalid, H. (2020). Big data analytics adoption: Determinants and performances among small to medium-sized enterprises. International Journal of Information Management, 54, 102190. https://doi.org/10.1016/j.ijinfomgt.2020.102190
Martín-Rojas, R., Garrido-Moreno, A., & García-Morales, V. J. (2023). Social media use, corporate entrepreneurship and organizational resilience: A recipe for SMEs success in a post-Covid scenario. Technological Forecasting and Social Change, 190, 122421. https://doi.org/10.1016/j.techfore.2023.122421
Mashat, R. M., Abourokbah, S. H., & Salam, M. A. (2024). Impact of internet of things adoption on organizational performance: a mediating analysis of supply chain integration, performance, and competitive advantage. Sustainability, 16(6), 2250. https://doi.org/10.3390/su16062250
Matthews, L., Hair, J., & Matthews, R. (2018). PLS-SEM: The holy grail for advanced analysis. Marketing management journal, 28(1), 1-13. https://doi.org/10.63963/001c.151119
Menegon, J., & Isatto, E. L. (2023). Digital twins as enablers of structure inspection and maintenance. Gestão & Produção, 30, e4922. https://doi.org/10.1590/1806-9649-2022v30e4922
Morchid, A., El Alami, R., Raezah, A. A., & Sabbar, Y. (2024). Applications of internet of things (IoT) and sensors technology to increase food security and agricultural Sustainability: Benefits and challenges. Ain Shams Engineering Journal, 15(3), 102509. https://doi.org/10.1016/j.asej.2023.102509
Novicka, J., & Volkova, T. (2025). Bridging big data analytics capability with sustainability business performance: a literature review. Sustainability, 17(6), 2362. https://doi.org/10.3390/su17062362
Okumu, S. A. (2022). Logistics Practices and Operational Performance of Fast-moving Consumer Goods Manufacturing Firms in Nairobi County. In. University of Nairobi. https://doi.org/http://erepository.uonbi.ac.ke/handle/11295/162643
Onesi-Ozigagun, O., Ololade, Y. J., Eyo-Udo, N. L., & Oluwaseun, D. (2024). Data-driven decision making: Shaping the future of business efficiency and customer engagement. International Journal of Multidisciplinary Research Updates, 7(2), 19-29. https://doi.org/10.53430/ijmru.2024.7.2.0031
Qaffas, A. A., Ilmudeen, A., Almazmomi, N. K., & Alharbi, I. M. (2023). The impact of big data analytics talent capability on business intelligence infrastructure to achieve firm performance. foresight, 25(3), 448-464. https://doi.org/10.1108/FS-01-2021-0002
Rahimazar, A., Nouri Qarahasanlou, A., Khanzadeh, D., & Tavaghi, M. (2024). Assessing resilience in mechanical systems: an industrial perspective. International Journal of Quality & Reliability Management, 41(9), 2452-2468. https://doi.org/10.1108/IJQRM-09-2022-0271
Rashed, M., Uddin, M. K., Islam, M. F., Mohsin, A., Rahman, S., Kumar, S., & Rana, J. (2025). Building organizational resilience in emerging economies: Strategic insights from Bangladesh. Sustainable Futures, 10, 101327. https://doi.org/10.1016/j.sftr.2025.101327
Rotsios, K., Folinas, D., Mouchtari, C., Andreou, A., Fotiadis, T., Folina, M.-T., & Gasteratos, A. (2025). Exploring the factors influencing the acceptance of IoT applications in food packaging. Foods, 14(4), 575. https://doi.org/10.3390/foods14040575
Sethi, M., Sushil, & Gupta, M. (2025). Modelling the enablers of organizational resilience: a modified total interpretive structural modeling (m-TISM) approach. Benchmarking: An International Journal, 32(5), 1776-1824. https://doi.org/10.1108/BIJ-09-2023-0621
Settembre-Blundo, D., González-Sánchez, R., Medina-Salgado, S., & García-Muiña, F. E. (2021). Flexibility and resilience in corporate decision making: a new sustainability-based risk management system in uncertain times. Global Journal of Flexible Systems Management, 22(Suppl 2), 107-132. https://doi.org/10.1007/s40171-021-00277-7
Shojaee, A., Rashed, M., Islam, M. F., & Vasa, L. (2025). Innovative configurations for organizational resilience: Bridging the proactive and reactive capability in volatile environments. Sustainable Futures, 10, 101236. https://doi.org/10.1016/j.sftr.2025.101236
Shoomal, A., Jahanbakht, M., Componation, P. J., & Ozay, D. (2024). Enhancing supply chain resilience and efficiency through internet of things integration: Challenges and opportunities. Internet of Things, 27, 101324. https://doi.org/10.1016/j.iot.2024.101324
Silva, A. A., & FERREIRA, F. C. (2017). Uncertainty, flexibility and operational performance of companies: modelling from the perspective of managers. RAM. Revista de Administração Mackenzie, 18, 11-38. https://doi.org/10.1590/1678-69712017/administracao.v18n4p11-38
Su, X., Zeng, W., Zheng, M., Jiang, X., Lin, W., & Xu, A. (2022). Big data analytics capabilities and organizational performance: the mediating effect of dual innovations. European Journal of Innovation Management, 25(4), 1142-1160. https://doi.org/10.1108/EJIM-10-2020-0431
Vadivel, S. R. S., Karthikeyan, V., & Gopalakrishnan, K. (2026). Introduction to the Internet of Things (IoT). In Internet of Things Security (pp. 3-31). Elsevier. https://doi.org/10.1016/B978-0-44-333759-8.00010-1
Vafaei-Zadeh, A., Nikbin, D., Danaraj, T., & Hanifah, H. (2025). Internet of Things adoption and manufacturing firms’ performance: the role of innovation capabilities. Journal of Manufacturing Technology Management. https://doi.org/10.1108/JMTM-11-2024-0610
Wehrle, E., Palomba, I., & Vidoni, R. (2021). Modeling, design and optimization of flexible mechanical systems. In (Vol. 11, pp. 7124). MDPI. https://doi.org/10.3390/app11157124
Werner, M. J. E., Yamada, A. P. L., Domingos, E. G. N., Leite, L. R., & Pereira, C. R. (2021). Exploring organizational resilience through key performance indicators. Journal of Industrial and Production Engineering, 38(1), 51-65. https://doi.org/10.1080/21681015.2020.1839582
Wided, R. (2023). IT capabilities, strategic flexibility and organizational resilience in SMEs post-COVID-19: A mediating and moderating role of big data analytics capabilities. Global Journal of Flexible Systems Management, 24(1), 123-142. https://doi.org/10.1007/s40171-022-00327-8
Xu, H., Wu, J., Pan, Q., Guan, X., & Guizani, M. (2023). A survey on digital twin for industrial internet of things: Applications, technologies and tools. IEEE Communications Surveys & Tutorials, 25(4), 2569-2598. https://doi.org/10.1109/COMST.2023.3297395
Zein, A., & Karimah, M. (2025). The Role of Internet of Things (IoT) in Enhancing Asset Management and Operational Efficiency. Dirya: Journal of Economic Management, 2(1), 1-8. https://doi.org/10.70283/dirya.v2i1.72
Zhang, Q., Vonderembse, M. A., & Lim, J.-S. (2003). Manufacturing flexibility: defining and analyzing relationships among competence, capability, and customer satisfaction. Journal of Operations Management, 21(2), 173-191. https://doi.org/10.1016/S0272-6963(02)00067-0
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Reports in Mechanical Engineering
This work is licensed under a Creative Commons Attribution 4.0 International License.