ENHANCING PROJECT MANAGEMENT EFFICIENCY THROUGH THE IVPO METHOD: EVIDENCE FROM MASTERGAZ
DOI:
https://doi.org/10.31732/2663-2209-2025-79-223-235Keywords:
IVPO method, project optimization, knapsack problem, multi-criteria decision-making, stakeholder satisfaction, performance metrics, ERP-BPMSAbstract
This study examines the Integrated Vector for Project Optimization (IVPO) method as an innovative solution to enhancing project management efficiency in complex engineering environments. The relevance of the research stems from the increasing need for adaptive decision-making models capable of handling resource constraints, multi-criteria evaluation, stakeholder dynamics, and real-time planning. The study aims to empirically validate the effectiveness of the IVPO method in reducing project completion time, improving budget adherence, and elevating stakeholder satisfaction. The methodology follows a mixed-methods research design, combining quantitative surveys and regression modeling with qualitative interviews conducted among project managers at Mastergaz. Five engineering projects, each under 100,000 USD, were analyzed using data from the ERP-BPMS BOS CIS platform. The IVPO method, rooted in the classical knapsack problem, introduces an optimization vector that integrates criteria such as time, cost, availability, risk, and skill alignment to generate efficient resource allocation scenarios. Findings indicate that IVPO implementation resulted in a 12% reduction in project duration, a 5% improvement in budget adherence, and a 4% increase in stakeholder satisfaction. Regression analysis confirmed statistically significant correlations between IVPO use and key performance indicators. The method also demonstrated enhanced decision transparency and operational efficiency across various project phases. Future research directions include scaling IVPO to manage larger project portfolios, integrating machine learning algorithms for automated weight calibration, and applying the method across diverse sectors such as IT, manufacturing, and infrastructure. This study contributes to the advancement of flexible, data-driven decision-support tools in the field of project management, offering a scalable solution to the challenges of contemporary project complexity.
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Abdel-Basset, M., Atef, A., & Smarandache, F. (2019). A hybrid neutrosophic multiple criteria group decision-making approach for project selection. Cognitive Systems Research, 57, 216-227. https://doi.org/10.1016/j.cogsys.2018.10.023
Albanese, M. (2022). Mixed methods in business, management and accounting research: An experimental design in the entrepreneurship domain. European Journal of Interdisciplinary Studies, 8(2), 35-48. https://doi.org/10.26417/641eff87
Almeida, F. (2018). Strategies to perform a mixed methods study. European Journal of Education Studies. https://doi.org/10.5281/zenodo.1406214
Amalnik, M. S., & Ravasan, A. Z. (2018). An investigation and classification of ERP project managers' required skills. International Journal of Service Science, Management, Engineering, and Technology, 9(1), 10-23. https://doi.org/10.4018/IJSSMET.2018010102
Anaya, C. R., Guaita, W., & Rodríguez Monroy, C. (2022). Model based on system dynamics for project portfolio management in industries. Journal of Applied Research and Technology, 20(3), 1122. https://doi.org/10.22201/icat.24486736e.2022.20.3.1122
Ansyah, R., Filcek, G., & Ramsey, D. M. (2023). Evaluating a computer application that aids multi-criteria decision making. Multiple Criteria Decision Making. https://doi.org/10.22367/mcdm.2023.18.03
Bahadorestani, A., Naderpajouh, N., & Sadiq, R. (2020). Planning for sustainable stakeholder engagement based on the assessment of conflicting interests in projects. Journal of Cleaner Production, 242, 118402. https://doi.org/10.1016/j.jclepro.2019.118402
Bai, L., Sun, Y., Shi, H., Shi, C., Bai, J., & Han, X. (2021). Dynamic assessment modelling for project portfolio benefits. Journal of the Operational Research Society, 73, 1596-1619. https://doi.org/10.1080/01605682.2021.1915193
Bai, L., Yang, M., Pan, T., & Sun, Y. (2023). Project portfolio selection and scheduling incorporating dynamic synergy. Kybernetes. https://doi.org/10.1108/k-04-2023-0694
Biloskurskyi, R. (2022). Agile methodology of implementation of ERP information systems. Scientific opinion: Economics and Management, 77, 12. https://doi.org/10.32836/2521-666x/2022-77-12
Chen, C. H. (2019). A New Multi-Criteria Assessment Model Combining GRA Techniques with Intuitionistic Fuzzy Entropy-Based TOPSIS Method for Sustainable Building Materials Supplier Selection. Sustainability. https://doi.org/10.3390/SU11082265
Chernenko, Y., Bedrii, D., Haidaienko, O., & Meliksetov, O. (2025). Mitigating operational risks in critical infrastructure through integrated ERP-BPMS: a multi-case study. Technology Audit and Production Reserves, 3(4(83)), 53–63. https://doi.org/10.15587/2706-5448.2025.330660
Chipulu, M., Ojiako, U., Marshall, A., & Williams, T. (2019). A dimensional analysis of stakeholder assessment of project outcomes. Production Planning & Control. https://doi.org/10.1080/09537287.2019.1567859
Cooper, R., & Sommer, A. F. (2023). Dynamic Portfolio Management for New Product Development. Research-Technology Management, 66(1), 19-31. https://doi.org/10.1080/08956308.2023.2183004
Davis, K. (2018). Reconciling the Views of Project Success. Project Management Journal, 49(6), 38–47. https://doi.org/10.1177/8756972818786663
Elkabalawy, M., & Moselhi, O. (2021). Optimized resource-constrained method for project schedule compression. Engineering, Construction and Architectural Management. https://doi.org/10.1108/ECAM-12-2020-1019
Grant, D. B., Shaw, S., Sweeney, E., Bahr, W., Chaisurayakarn, S., & Evangelista, P. (2023). Using mixed methods in logistics and supply chain management research: Current state and future directions. The International Journal of Logistics Management. https://doi.org/10.1108/ijlm-04-2023-0156
Hewlett, L., & Werbeloff, M. (2022). Preparing public management students for mixed methods research. Teaching Public Administration. https://doi.org/10.1177/01447394221110339
Ibrahim, S., Duraisamy, S., & Sridevi, U. (2019). Flexible and reliable ERP project customization framework to improve user satisfaction level. Cluster Computing, 1-7. https://doi.org/10.1007/s10586-017-1664-z
Ivchenko, I., Mykheliev, I. L., Farionova, T. A., Knyrik, N. R., & Marshak, O. I. (2024). Modeling optimization tasks in IT project management. Electrical and Computer Systems, 40. https://doi.org/10.15276/eltecs.40.116.2024.3
Jang, H., & Suh, E. S. (2025). Technology Infusion Analysis‐Based Research and Development Project Portfolio Valuation. Systems Engineering. https://doi.org/10.1002/sys.21817
Kandakoglu, M., Walther, G., & Amor, S. B. (2023). The use of multi-criteria decision-making methods in project portfolio selection: A literature review and future research directions. Annals of Operations Research, 332, 807-830. https://doi.org/10.1007/s10479-023-05564-3
Kolasa, I., & Modrzejewska, D. (2020). How Information System Project Stakeholders Perceive Project Success. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-030-52249-0_36
Kraljic, A., & Kraljic, T. (2019). Agile software engineering practices in ERP implementation. Advances in Intelligent Systems and Computing, 279-290. https://doi.org/10.1007/978-3-030-44322-1_21
Langston, C. A., Ghanbaripour, A., & Abu Arqoub, M. (2018). Measuring project success: conceptualizing a new approach applicable to all project types. In K. Do, M. Sutrisna, B. Cooper-Cooke, & O. Olatunji (Eds.), AUBEA 2018 Conference Proceedings, Vol 1: Innovation (Vol. 1, pp. 107-120). Curtin University of Technology. https://docs.wixstatic.com/ugd/94be57_a1986413edcf4b18aec5aab332b8883b.pdf
Lucien, N. I., & Amolo, A. E. J. (2025). Stakeholder Engagement Strategies and Road Construction Project Performance. International Journal of Finance & Banking Studies (2147-4486), 14(1), 68–78. https://doi.org/10.20525/ijfbs.v14i1.3977
Mansor, M. A. (2025). Multi-Criteria Decision Making for Prioritizing Project Manager Skills according to Construction Project Success Factors. Engineering, Technology & Applied Science Research, 15(2), 21861–21875. https://doi.org/10.48084/etasr.10083
Manzolli, J. A., Yu, J., & Miranda-Moreno, L. (2025). Synthetic multi-criteria decision analysis (S-MCDA): A new framework for participatory transportation planning. Transportation Research Interdisciplinary Perspectives, 31, 101463. https://doi.org/10.1016/j.trip.2025.101463
Marcondes, G. (2019). Project Portfolio Selection Considering Return-risk Evaluation and Multiple-Criteria Decision Analysis. Proceedings of the International Conference on Decision Support System Technology, 264-269. https://doi.org/10.5220/0007350802640269
Mishra, G., & Mishra, L. (2021). Applications of optimization techniques in construction management. EPRA International Journal of Research and Development, 468–474. https://doi.org/10.36713/EPRA6916
Nguyen, T. S., & Mohamed, S. (2020). Mediation Effect of Stakeholder Management Between Stakeholder Characteristics and Project Performance. Journal of Engineering, Project, and Production Management, 11(2), 102–117. https://doi.org/10.2478/jeppm-2021-0011
Nguyen, V. D., Thuc, L., & Tran, H.-B. (2021). Assessing stakeholder satisfaction in PPP transport projects in developing countries: Evidence from Vietnam. Built Environment Project and Asset Management. https://doi.org/10.1108/bepam-08-2021-0106
Nhung, H., Hai, V. V., Silhavy, P., Prokopova, Z., & Silhavy, R. (2023). Incorporating statistical and machine learning techniques into the optimization of correction factors for software development effort estimation. Journal of Software: Evolution and Process. https://doi.org/10.1002/smr.2611
Olatunde, N., & Odeyinka, H. (2020). Factors Influencing Stakeholder Management in Building Projects Procured by Private Corporate Organisations. Journal of Engineering, Project, and Production Management, 11(1), 18-29. https://doi.org/10.2478/jeppm-2021-0002
Ozkan, B., Koops, M., Türetken, O., & Reijers, H. A. (2023). The Influence of Business Process Management System Implementation on an Organization’s Process Orientation: A Case Study of a Financial Service Provider. Information Systems Management, 41(4), 377–398. https://doi.org/10.1080/10580530.2023.2286980
Peng, J., Su, Z., & Liu, X. (2025). Multi skill project scheduling optimization based on quality transmission and rework network reconstruction. Scientific Reports, 15(1). https://doi.org/10.1038/s41598-025-92342-9
Poth, C., Kierstead, M., Georgiou, G., & Mack, E. (2024). Mixed methods research teams: leveraging integrative teamwork for addressing complex problems. Frontiers in Education, 9. https://doi.org/10.3389/feduc.2024.1356629
Rad, F. H., & Rowzan, S. M. (2018). Designing a hybrid system dynamic model for analyzing the impact of strategic alignment on project portfolio selection. Simulation Modelling Practice and Theory, 89, 175-194. https://doi.org/10.1016/j.simpat.2018.10.001
Salama, T., & Moselhi, O. (2019). Multi-objective optimization for repetitive scheduling under uncertainty. Engineering, Construction and Architectural Management. https://doi.org/10.1108/ECAM-05-2018-0217
Saleh, S., Ahmed, S. K., & Nashat, F. (2020). A genetic algorithm for solving an optimization problem: Decision-making in project management. 2020 International Conference on Computer Science and Software Engineering (CSASE), 221–225. https://doi.org/10.1109/CSASE48920.2020.9142054
Song, J., Munyinda, M., & Adu Sarfo, P. (2025). Examining the impact of risk management practices on sustainable project performance in the construction industry: the role of stakeholder engagement. Frontiers in Built Environment, 11. https://doi.org/10.3389/fbuil.2025.1575827
Sperry, R., & Jetter, A. (2019). A Systems Approach to Project Stakeholder Management: Fuzzy Cognitive Map Modeling. Project Management Journal, 50(6), 699-715. https://doi.org/10.1177/8756972819847870
Timans, R., Wouters, P., & Heilbron, J. (2019). Mixed methods research: What it is and what it could be. Theory and Society, 48, 193-216. https://doi.org/10.1007/S11186-019-09345-5
Tsesliv, O. (2022). Economical and mathematical methods of project management. 2022 IEEE 3rd International Conference on System Analysis & Intelligent Computing (SAIC). https://doi.org/10.1109/SAIC57818.2022.9922987
Valentini, C., Munnukka, J., & Zhao, H. (2024). Stakeholder satisfaction with corporate conflict engagement actions: Exploring the effects of goodwill, trust, and value alignment. Business Horizons, 67(6), 797–813. https://doi.org/10.1016/j.bushor.2024.08.003
Vinogradova, I. (2019). Multi-attribute decision-making methods as a part of mathematical optimization. Mathematics, 7(10), 915. https://doi.org/10.3390/math7100915
Vuorinen, L., & Martinsuo, M. (2019). Value-oriented stakeholder influence on infrastructure projects. International Journal of Project Management. https://doi.org/10.1016/j.ijproman.2018.10.003
Wu, J. (2021). Efficient management system of construction engineering industry based on ERP. 2021 International Conference on Wireless Communications and Smart Grid (ICWCSG), 346-349. https://doi.org/10.1109/ICWCSG53609.2021.00075
Zahedirad, M., Ghezavati, V., Khalili-Damghani, K., & Komijan, A. R. (2025). Solving an Integrated Project Portfolio Selection and Contractor Selection Problem: Fuzzy Goal Programming Based on Fuzzy Preference Relations. Fuzzy Information and Engineering, 17(1), 75–107. https://doi.org/10.26599/fie.2025.9270054
Zhao, X., & Lu, R. (2025). Dynamic scheduling optimization model and algorithm for linear projects considering local rescheduling. Engineering, Construction and Architectural Management. https://doi.org/10.1108/ecam-07-2024-0986
Zhou, R. (2023). Research on engineering project schedule optimization method based on HRRN. 2023 International Conference on Electronics and Devices, Computational Science (ICEDCS). https://doi.org/10.1109/ICEDCS60513.2023.00055
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