Optimization of Mechanical Companies Production Performance through the Operations Management Models: Moderating Role of Technology Capability
DOI:
https://doi.org/10.31181/rme569Keywords:
Operations Management Models, Technology Capability, Mechanical Companies, OptimizationAbstract
The research aim to test the optimization of production performance through operations management models of mechanical companies. Moderating effect of technology capabilities also tested. Cross sectional quantitative data was collected from the 450 mechanical company’s employees employing convenient sampling technique. Both of the descriptive and inferential statistics were conducted using SPSS and Smart PLS respectively. The results shown that all operations management models have positive and significant impact on the production performance of mechanical companies. From the direct effects, ERP has more effect on production performance which is showing the critical importance of integrated information systems in improving production planning, resource coordination, and real-time decision-making. While six sigma and JIT also has positive significant impact on production performance. Balance scorecard also significantly contributed to increase the production performance. Moderating effect results also confirmed that technology capability positively strengthens the relationship between operation management models and production performance. Study with significant finding highlighted the significance of combining managerial practices with technological readiness to achieve superior mechanical company’s performance. The research theoretically also contributed to operations management literature through demonstrating that production performance is enhanced through the integrated adoption of lean, quality, strategic, and digital management systems. From the practical aspect, research also suggested that mechanical organizations should invest in digital transformation, quality improvement programs, and technological capability development to sustain long-term operational competitiveness.
References
Abobakr, M. A., Abdel-Kader, M., & Elbayoumi, A. F. (2023). Integrating S-ERP systems and lean manufacturing practices to improve sustainability performance: an institutional theory perspective. Journal of Accounting in Emerging Economies, 13(5), 870-897. https://doi.org/10.1108/JAEE-10-2020-0255
Abobakr, M. A., Abdel-Kader, M., & F. Elbayoumi, A. F. (2024). An experimental investigation of the impact of sustainable ERP systems implementation on sustainability performance. Journal of Financial Reporting and Accounting. https://doi.org/10.1108/JFRA-04-2023-0207
Achibat, F. E., Lebkiri, A., Lougraimzi, H., Berrid, N., & Maqboul, A. (2023). Analysis of the impact of six sigma and lean manufacturing on the performance of companies. Management Systems in Production Engineering, 31(2), 191-196. https://doi.org/10.2478/mspe-2023-0020
Agyabeng-Mensah, Y., Afum, E., Agnikpe, C., Cai, J., Ahenkorah, E., & Dacosta, E. (2021). Exploring the mediating influences of total quality management and just in time between green supply chain practices and performance. Journal of Manufacturing Technology Management, 32(1), 156-175. https://doi.org/10.1108/JMTM-03-2020-0086
Ahmad, I., AlFaify, S. A., Alanezi, K. M., Alfaifi, M. Q., Abduljawad, M. M., & Liu, Y. (2025). Improved hydrogen production performance of an S-scheme Nb 2 O 5/La 2 O 3 photocatalyst. Dalton Transactions, 54(4), 1402-1417. https://doi.org/10.1039/D4DT02913E
Ahmed, A., Olsen, J., & Page, J. (2023). Integration of Six Sigma and simulations in real production factory to improve performance–a case study analysis. International Journal of Lean Six Sigma, 14(2), 451-482. https://doi.org/10.1108/IJLSS-06-2021-0104
Akram, H., Abdelrady, A. H., Al-Adwan, A. S., & Ramzan, M. (2022). Teachers’ perceptions of technology integration in teaching-learning practices: A systematic review. Frontiers in psychology, 13, 920317. https://doi.org/10.3389/fpsyg.2022.920317
Al-Assaf, K., Alzahmi, W., Ahmed, V., & Bahroun, Z. (2025). Comprehensive Review of Enterprise Resource Planning (ERP) Systems And Performance Management Integration In Healthcare. Management Systems in Production Engineering. https://doi.org/10.2478/mspe-2025-0032
Albuhisi, A. M., & Abdallah, A. B. (2018). The impact of soft TQM on financial performance: the mediating roles of non-financial balanced scorecard perspectives. International Journal of Quality & Reliability Management, 35(7), 1360-1379. https://doi.org/10.1108/IJQRM-03-2017-0036
Andrade-Rojas, M. G., Kathuria, A., & Lee, H.-H. (2024). Multilevel synergy of information technology for operational integration: competition networks and operating performance. Production and Operations Management, 33(5), 1116-1141. https://doi.org/10.1177/10591478241239005
Anumala, K. (2021). Examining the relationship between supply chain management practices and production performance in Indian handloom industry. International Journal of System Dynamics Applications (IJSDA), 10(2), 53-72. https://doi.org/10.4018/IJSDA.2021040104
Asgharian, H., Iov, F., Nielsen, M. P., Liso, V., Burt, S., & Baxter, L. (2025). Analysis of cryogenic CO2 capture technology integrated with Water-Ammonia Absorption refrigeration cycle for CO2 capture and separation in cement plants. Separation and Purification Technology, 353, 128419. https://doi.org/10.1016/j.seppur.2024.128419
Attneave, F., & Arnoult, M. D. (1956). The quantitative study of shape and pattern perception. Psychological Bulletin, 53(6), 452. https://doi.org/10.1037/h0044049
Azad, M. A. (2025). Evaluating the role of lean manufacturing in reducing production costs and enhancing efficiency in textile mills. Authorea Preprints. https://doi.org/10.36227/techrxiv.175459830.02641032/v1
Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of management, 17(1), 99-120. https://doi.org/10.1177/0149206391017001
Cebekhulu, B., & Ozor, P. (2022). The influence of quality management and ERP systems on organisational culture and performance. Proceedings on Engineering Sciences, 4(1), 41-50. https://doi.org/10.24874/PES04.01.007
Chehimi, M., & Naro, G. (2024). Balanced Scorecards and sustainability Balanced Scorecards for corporate social responsibility strategic alignment: A systematic literature review. Journal of environmental management, 367, 122000. https://doi.org/10.1016/j.jenvman.2024.122000
Chinta, P. C. R. (2022). Enhancing supply chain efficiency and performance through ERP optimisation strategies. Journal of Artificial Intelligence & Cloud Computing, 1(4), 10.47363. https://doi.org/10.47363/JAICC/2022(1)418
Chopra, R., Sawant, L., Kodi, D., & Terkar, R. (2022). Utilization of ERP systems in manufacturing industry for productivity improvement. Materials Today: Proceedings, 62, 1238-1245. https://doi.org/10.1016/j.matpr.2022.04.529
Cruz-Torres, W., Alvarez-Risco, A., & Del-Aguila-Arcentales, S. (2021). Impact of Enterprise Resource Planning (ERP) implementation on performance of an education enterprise: a Structural Equation Modeling (SEM). Studies in Business and Economics, 16(2), 37-52. https://doi.org/10.2478/sbe-2021-0023
Daniyan, I., Adeodu, A., Mpofu, K., Maladzhi, R., & Katumba, M. G. K.-K. (2022). Application of lean Six Sigma methodology using DMAIC approach for the improvement of bogie assembly process in the railcar industry. Heliyon, 8(3). https://doi.org/10.1016/j.heliyon.2022.e09043
Dewi, D. R. S., Hermanto, Y. B., Tait, E., & Sianto, M. E. (2023). The product–service system supply chain capabilities and their impact on sustainability performance: a dynamic capabilities approach. Sustainability, 15(2), 1148. https://doi.org/10.3390/su15021148
Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of convenience sampling and purposive sampling. American journal of theoretical and applied statistics, 5(1), 1-4. https://doi.org/10.11648/j.ajtas.20160501.11
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
Fransisca, L., Renaldo, N., Chandra, T., Augustine, Y., & Musa, S. (2025). Digital Innovation Capability and Customer Value Co-Creation on New Product Performance with Digital Transformation Maturity as a Moderating Variable in Trading Companies in Indonesia. Luxury: Landscape of Business Administration, 3(1), 1-15. https://doi.org/10.61230/luxury.v3i1.103
Fullerton, R. R., & McWatters, C. S. (2001). The production performance benefits from JIT implementation. Journal of Operations Management, 19(1), 81-96. https://doi.org/10.1016/S0272-6963(00)00051-6
García-Cutrín, J., & Rodríguez-García, C. (2024). Enhancing corporate sustainability through Just-In-Time (JIT) practices: A meta-analytic examination of financial performance outcomes. Sustainability, 16(10), 4025. https://doi.org/10.3390/su16104025
Golzar, J., Noor, S., & Tajik, O. (2022). Convenience sampling. International Journal of Education & Language Studies, 1(2), 72-77. https://doi.org/10.22034/ijels.2022.162981
Gomaa, A. H. (2025). Optimizing Machining Process Performance Using Lean Six Sigma: A Case Study. Transnational Supply Chain Research, 1(1), 52-81. https://doi.org/10.65773/tscr.1.1.46
Gomaa, A. H. (2026). Enhancing shutdown maintenance performance using Lean Six Sigma: a case study. International Journal of Lean Six Sigma, 17(2), 743-781. https://doi.org/10.1108/IJLSS-03-2024-0043
Haekal, J. (2023). Performance assessment of wheat flour suppliers based on balanced scorecard (BSC). International Journal of Scientific and Applied Research (IJSAR), eISSN: 2583-0279, 3(2), 24-33. https://doi.org/10.54756/IJSAR.2023.V3.2.3
Hair, J., Hollingsworth, C. L., Randolph, A. B., & Chong, A. Y. L. (2017). An updated and expanded assessment of PLS-SEM in information systems research. Industrial Management & Data Systems, 117(3), 442-458. https://doi.org/10.1108/IMDS-04-2016-0130
Hair Jr, J. F., Matthews, L. M., Matthews, R. L., & Sarstedt, M. (2017). PLS-SEM or CB-SEM: updated guidelines on which method to use. International Journal of multivariate data analysis, 1(2), 107-123. https://doi.org/10.1504/IJMDA.2017.087624
HAMID, N. A. (2022). The impact of TQM on business performances based on balanced scorecard approach in Malaysia SMEs. International Journal for Quality Research. https://doi.org/10.24874/IJQR16.01-16
Hanaysha, J., & Alzoubi, H. (2022). Investigating the impact of benefits and challenges of IOT adoption on supply chain performance and organizational performance: An empirical study in Malaysia. Uncertain Supply Chain Management, 10(2), 537-550. https://doi.org/10.5267/j.uscm.2021.11.009
He, S., Manns, G., Saunders, J., Wang, W., Pollock, L., & Soffa, M. L. (2019). A statistics-based performance testing methodology for cloud applications. Proceedings of the 2019 27th ACM Joint Meeting on European software engineering conference and symposium on the foundations of software engineering, 188-199. https://doi.org/10.1145/3338906.3338912
Helo, P., & Hao, Y. (2022). Artificial intelligence in operations management and supply chain management: an exploratory case study. Production Planning & Control, 33(16), 1573-1590. https://doi.org/10.1080/09537287.2021.1882690
Hristov, I., Cristofaro, M., Camilli, R., & Leoni, L. (2024). A system dynamics approach to the balanced scorecard: a review and dynamic strategy map for operations management. Journal of Manufacturing Technology Management, 35(4), 705-743. https://doi.org/10.1108/JMTM-02-2022-0069
Hsiao, M.-H. (2024). Resource integration and firm performance through organizational capabilities for digital transformation. Digital Transformation and Society. https://doi.org/10.1108/DTS-07-2023-0050
Huang, J., Irfan, M., Fatima, S. S., & Shahid, R. M. (2023). The role of lean six sigma in driving sustainable manufacturing practices: an analysis of the relationship between lean six sigma principles, data-driven decision making, and environmental performance. Frontiers in Environmental Science, 11, 1184488. https://doi.org/10.3389/fenvs.2023.1184488
Jackson, I., Ivanov, D., Dolgui, A., & Namdar, J. (2024). Generative artificial intelligence in supply chain and operations management: a capability-based framework for analysis and implementation. International Journal of Production Research, 62(17), 6120-6145. https://doi.org/10.1080/00207543.2024.2309309
Jum'a, L., & Bushnaq, M. (2024). Investigating the role of flexibility as a moderator between supply chain integration and firm performance: the case of manufacturing sector. Journal of Advances in Management Research, 21(2), 203-227. https://doi.org/10.1108/JAMR-07-2023-0188
Kamble, S. S., Gunasekaran, A., Subramanian, N., Ghadge, A., Belhadi, A., & Venkatesh, M. (2023). Blockchain technology’s impact on supply chain integration and sustainable supply chain performance: Evidence from the automotive industry. Annals of Operations Research, 327(1), 575-600. https://doi.org/10.1007/s10479-021-04129-6
Kaplan, R. S., & Norton, D. P. (1996). Using the balanced scorecard as a strategic management system. https://shortlink.uk/1s07n
Kaufmann, T. (2024). Strategiekarte und Balanced Scorecard (RS Kaplan und DP Norton). In Strategiewerkzeuge aus der Praxis: Band 2: Optionenfindung, Strategieentwicklung und Umsetzung (pp. 197-236). Springer. https://doi.org/10.1007/978-3-662-68897-7
Lara, A. C., Menegon, E. M. P., Sehnem, S., & Kuzma, E. (2022). Relationship between just in time, lean manufacturing, and performance practices: a meta-analysis. Gestão & Produção, 29, e9021. https://doi.org/10.1590/1806-9649-2022v29e9021
Lee, K. L., Wong, S. Y., Alzoubi, H. M., Al Kurdi, B., Alshurideh, M. T., & El Khatib, M. (2023). Adopting smart supply chain and smart technologies to improve operational performance in manufacturing industry. International Journal of Engineering Business Management, 15, 18479790231200614. https://doi.org/10.1177/18479790231200614
Lu, M., & Shen, Z. J. M. (2021). A review of robust operations management under model uncertainty. Production and Operations Management, 30(6), 1927-1943. https://doi.org/10.1111/poms.13239
Mehmood, K., Zia, A., Alkatheeri, H. B., Jabeen, F., & Zhang, H. (2023). Resource-based view theory perspective of information technology capabilities on organizational performance in hospitality firms: a time-lagged investigation. Journal of Hospitality and Tourism Technology, 14(5), 701-716. https://doi.org/10.1108/JHTT-05-2021-0149
Mio, C., Costantini, A., & Panfilo, S. (2022). Performance measurement tools for sustainable business: A systematic literature review on the sustainability balanced scorecard use. Corporate social responsibility and environmental management, 29(2), 367-384. https://doi.org/10.1002/csr.2206
Mittal, A., Gupta, P., Kumar, V., Al Owad, A., Mahlawat, S., & Singh, S. (2023). The performance improvement analysis using Six Sigma DMAIC methodology: A case study on Indian manufacturing company. Heliyon, 9(3). https://doi.org/10.1016/j.heliyon.2023.e14625
Mukhtar, B., Shad, M. K., & Lai, F. W. (2025). Fostering sustainability performance in the Malaysian manufacturing companies: the role of green technology innovation and innovation capabilities. Benchmarking: An International Journal, 32(3), 992-1016. https://doi.org/10.1108/BIJ-07-2023-0468
Nasution, M. D. T. P., Rossanty, Y., Harahap, R., Tanjung, A. R., & Nasution, T. A. M. (2026). Technology-Driven Resource Utilization and Integration to Enhance Firm Performance. Aptisi Transactions on Technopreneurship (ATT), 8(1), 268− 283-268− 283. https://doi.org/10.34306/att.v8i1.472
Nugraha, A. T., Wahyudi, R., Fawzi, A. M., & Sunarti, S. (2022). Eco Design, Internal Environment Management, Just in Time and Organizational Performance: Examining Moderating Role of Trust: Examining Moderating Role of Trust. Jurnal Manajemen Indonesia, 22(3), 396-405. https://doi.org/10.25124/jmi.v22i3.3673
Othman, A. A., Abd Rahman, S., Sundram, V. P. K., & Bhatti, M. A. (2015). Modelling marketing resources, procurement process coordination and firm performance in the Malaysian building construction industry. Engineering, Construction and Architectural Management, 22(6), 644-668. https://doi.org/10.1108/ECAM-02-2014-0030
Porter, M. E. (1991). Towards a dynamic theory of strategy. Strategic management journal, 12(S2), 95-117. https://doi.org/10.1002/smj.4250121008
Pratiwi, N. A., Susilowati, E., Syukriah, S., Pianda, D., & Susanti, E. (2023). Quality Performance of Manufacturing Companies in West Java: SCM, TQM, and JIT Impact. Jurnal Informatika Ekonomi Bisnis, 785-790. https://doi.org/10.37034/infeb.v5i3.646
Priliska, A. D., Kurniadewi, M., & Winarno, F. S. (2023). Building competitive advantage through strategy map and balanced scorecard in improving company performance. Devotion: Journal of Research and Community Service, 4(7). https://doi.org/10.59188/devotion.v4i7.520
Quesado, P., Marques, S., Silva, R., & Ribeiro, A. (2022). The balanced scorecard as a strategic management tool in the textile sector. Administrative Sciences, 12(1), 38. https://doi.org/10.3390/admsci12010038
Quezada, L. E., Aguilera, D. E., Palominos, P. I., & Oddershede, A. M. (2022). An ANP model to generate performance indicators for manufacturing firms under a balanced scorecard approach. Engineering Management Journal, 34(1), 70-84. https://doi.org/10.1080/10429247.2020.1840877
Rashid, A., Rasheed, R., & Amirah, N. A. (2025). Synergizing TQM, JIT, and green supply chain practices: strategic insights for enhanced environmental performance. Logistics, 9(1), 18. https://doi.org/10.3390/logistics9010018
Ruhiyat, R. F., Pradesa, H. A., Novira, A., & Wijayanti, R. (2025). Implementation of the Balanced Scorecard for Performance Evaluation at the West Java Provincial Plantation Service. Jurnal Manajemen dan Perbankan (JUMPA), 12(1), 14-27. https://doi.org/10.55963/jumpa.v12i1.729
Sahoo, S., & Upadhyay, A. (2025). Improving triple bottom line (TBL) performance: analyzing impacts of industry 4.0, lean six sigma and circular supply chain management. Annals of Operations Research, 355(1), 951-982. https://doi.org/10.1007/s10479-024-05945-2
Saihi, A., Ben-Daya, M., & Hariga, M. (2025). The moderating role of technology proficiency and academic discipline in AI-chatbot adoption within higher education: Insights from a PLS-SEM analysis. Education and Information Technologies, 30(5), 5843-5881. https://doi.org/10.1007/s10639-024-13023-0
Salah, A., Çağlar, D., & Zoubi, K. (2023). The impact of production and operations management practices in improving organizational performance: The mediating role of supply chain integration. Sustainability, 15(20), 15140. https://doi.org/10.3390/su152015140
Saraswat, P., Agrawal, R., & Rane, S. B. (2025). Technological integration of lean manufacturing with industry 4.0 toward lean automation: insights from the systematic review and further research directions. Benchmarking: An International Journal, 32(6), 1909-1941. https://doi.org/10.1108/BIJ-05-2023-0316
Shish, Z. H., & Shafa, H. (2023). A Quantitative Study On IT-Enabled ERP Systems And Their Role In Operational Efficiency. International Journal of Scientific Interdisciplinary Research, 4(4), 62-99. https://doi.org/10.63125/nbpyce10
Siddiqui, A. (2022). The importance of just in time (JIT) methodology and its advantages in health care quality management business–A scoping review. Biomedical Journal of Scientific & Technical Research, 42(1), 33317-33325. https://doi.org/10.26717/BJSTR.2022.42.006701
Tagkouta, E., Psycharis, P. N., Psarras, A., Anagnostopoulos, T., & Salmon, I. (2023). Predicting success for web product through key performance indicators based on balanced scorecard with the use of machine learning. WSEAS Transactions on Business and Economics, 20, 646-656. https://doi.org/10.37394/23207.2023.20.59
Talo, M. C., & Emanuel, A. W. R. (2025). Systematic Review of Enterprise Resource Planning (ERP) System Implementation in Organizations: Challenges and Successes to Company Performance. Bitnet: Jurnal Pendidikan Teknologi Informasi, 10(2), 1-11. https://doi.org/10.33084/bitnet.v10i2.9603
Tao, J., Ge, Y., Liang, R., Sun, Y., Cheng, Z., Yan, B., & Chen, G. (2022). Technologies integration towards bio-fuels production: a state-of-the-art review. Applications in Energy and Combustion Science, 10, 100070. https://doi.org/10.1016/j.jaecs.2022.100070
Trivedi, Y., Sharma, M., Mishra, R. K., Sharma, A., Joshi, J., Gupta, A. B., Achintya, B., Shah, K., & Vuppaladadiyamd, A. K. (2025). Biochar potential for pollutant removal during wastewater treatment: A comprehensive review of separation mechanisms, technological integration, and process analysis. Desalination, 600, 118509. https://doi.org/10.1016/j.desal.2024.118509
Tuli, F. A., & Kaluvakuri, S. (2022). Implementation of ERP systems in organizational settings: enhancing operational efficiency and productivity. Asian Business Review, 12(3), 89-96. https://doi.org/10.18034/abr.v12i3.676
Utama, D. M., & Abirfatin, M. (2023). Sustainable Lean Six-sigma: A new framework for improve sustainable manufacturing performance. Cleaner engineering and technology, 17, 100700. https://doi.org/10.1016/j.clet.2023.100700
Velaga, V. (2022). Enhancing Supply Chain Efficiency and Performance Through ERP Optimization Strategies. https://doi.org/10.47363/JAICC/2022(1)418
Vidan, A., & Fiedler, L. (2023). A composable just-in-time programming framework with LLMs and FBP. 2023 IEEE High Performance Extreme Computing Conference (HPEC), 1-8. https://doi.org/10.1109/HPEC58863.2023.10363587
Wahjudi, D., & Palit, H. N. (2024). Enhancing Organizational Performance Through Integrated ERP-Based Balanced Scorecard Systems: A Case Study. KnE Social Sciences. https://doi.org/10.18502/kss.v9i32.17430
Zainab, B., Awais Bhatti, M., & Alshagawi, M. (2017). Factors affecting e-training adoption: An examination of perceived cost, computer self-efficacy and the technology acceptance model. Behaviour & Information Technology, 36(12), 1261-1273. https://doi.org/10.1080/0144929X.2017.1380703
Zhang, B., Guo, T., Qu, Z., Wang, J., Chen, M., & Liu, X. (2023). Numerical simulation of fracture propagation and production performance in a fractured geothermal reservoir using a 2D FEM-based THMD coupling model. Energy, 273, 127175. https://doi.org/10.1016/j.energy.2023.127175
Zhang, T., Shi, Z.-Z., Shi, Y.-R., & Chen, N.-J. (2022). Enterprise digital transformation and production efficiency: Mechanism analysis and empirical research. Economic research-Ekonomska istraživanja, 35(1), 2781-2792. https://doi.org/10.1080/1331677X.2021.1980731
Zhang, Y., Qiu, J., Zhu, B., Fedin, M., Cheng, B., Yu, J., & Zhang, L. (2022). ZnO/COF S-scheme heterojunction for improved photocatalytic H2O2 production performance. Chemical Engineering Journal, 444, 136584. https://doi.org/10.1016/j.cej.2022.136584
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Reports in Mechanical Engineering

This work is licensed under a Creative Commons Attribution 4.0 International License.