Control and Optimization in Applied Mathematics

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AHP-Based Framework for Optimizing, and Decision-Support in Enterprise Architecture Implementation

Articles in Press

Document Type : Research Article

Authors

1 Faculty of Engineering, Department of Computer Engineering, Imam Reza International University, Mashhad, Iran

2 Department of Computer and Information Technology Engineering, Payame Noor University (PNU), Iran

10.30473/coam.2025.74499.1308

Abstract

Enterprise architecture (EA) offers an integrated framework for strategic planning and organizational governance. Implementing EA effectively requires prioritizing a concise set of criteria within a complex system, leveraging mathematical modeling and optimization to inform decisions under uncertainty. This study introduces a hierarchical decision-making approach using Analytic Hierarchy Process (AHP) to extract and weight the most impactful criteria from an extensive literature base and expert opinions, with a focus on control-theoretic and optimization perspectives. Using insights from 18 experts from various fields and the proposed approach, key criteria of successful enterprise architecture deployment were identified and quantified: commitment (0.1143), governance (0.1082), infrastructure (0.0751), organizational management (0.0589), and senior management support (0.0484). The methodology integrates weights with objective-function considerations, sensitivity analyses, and optimization-oriented interpretations to ensure robust prioritization under uncertainty. The resulting framework supports decision-makers in (i) controlling and steering EA initiatives, (ii) optimizing resource allocation and process efficiencies, and (iii) designing data-driven, scenario-based decision models for dynamic organizational environments. These findings offer actionable guidance for managers aiming to enhance performance, reduce costs, and secure competitive advantage through disciplined governance, rigorous modeling, and evidence-based decision support.

Highlights

  • Proposes a structured, optimization-oriented decision framework for enterprise architecture (EA) implementation that integrates Analytic Hierarchy Process (AHP) with control-theoretic and objective-function considerations under uncertainty.
  • Synthesizes evidence from an extensive literature review and expert judgment (18 domain specialists) to systematically extract, screen, and prioritize EA success criteria within a hierarchical decision model.
  • Identifies and quantitatively ranks the most influential EA implementation criteria, with commitment, governance, infrastructure, organizational management, and senior management support emerging as dominant drivers of success.
  • Demonstrates how weighted EA criteria can be interpreted within sensitivity analysis and optimization perspectives to support robust, data-driven, and scenario-based managerial decision-making.
  • Provides actionable insights for decision-makers to improve governance quality, optimize resource allocation, and enhance organizational performance through disciplined, mathematically informed EA planning.

Keywords

Main Subjects

References
[1] Aier, S., Schelp, J. (2010). “A reassessment of enterprise architecture implementation”. In Service-Oriented Computing. ICSOC/ServiceWave 2009 Workshops: International Workshops, ICSOC/ServiceWave 2009, Stockholm, Sweden, November 23-27, 2009, Revised Selected Papers 2 (pp. 35-47). Springer Berlin Heidelberg, doi: https://doi.org/10.1007/978-3-642-16132-2_4.
[2] Ansyori, R., Qodarsih, N., Soewito, B. (2018). “A systematic literature review: Critical success factors to implement enterprise architecture”. Procedia Computer Science, 135, 43-51, doi: https://doi.org/10.1016/j.procs.2018.08.148.
[3] Alghamdi, H. (2025). “Integrating emerging technologies into enterprise architecture: Challenges and opportunities”. Access Journal, 6(1), 8-24, doi: https://doi.org/10.46656/access.2025.6.1(1).
[4] Baby, S. (2013). “AHP modeling for multicriteria decision-making and to optimise strategies for protecting coastal landscape resources”. International Journal of Innovation, Management and Technology, 4(2), 218-227, doi: https://doi.org/10.7763/IJIMT.2013.V4.395.
[5] Hadaya, P., Gagnon, B. (2017). “Business architecture: The missing link in strategy formulation, implementation and execution”. ASATE Publishing Inc.
[6] Heydari, A., Yousefzadeh, H.R. (2016). “A new measure for evaluating the efficiency of human’s resources in university”. Control and Optimization in Applied Mathematics, 1(1), 41-53.
[7] Kamogawa, T., Okada, H. (2008). “Enterprise architecture and information systems: In Japanese banking industry”. In 2008 International Symposium on Applications and the Internet (pp. 433-436), IEEE, doi: https://doi.org/10.1109/SAINT.2008.66.
[8] Kerr, D. McMillan, A. (2015). “Challenges in enterprise architecture: User perspectives”. International Journal of Information Systems and Project Management, 3(4), 19-32.
[9] Khairina, D.M., Purwanto, P., Nugraheni, D.M.K. (2024). “Systematic literature review on evaluation models and methods in enterprise architecture research”. Bulletin of Electrical Engineering and Informatics, 13(4), 2851-2864, doi: https://doi.org/10.11591/eei.v13i4.6943.
[10] Kurnia, S., Kotusev, S. (2021). “The role of enterprise architecture for digital transformations”. Sustainability, 13(4), 2237, doi: https://doi.org/10.3390/su13042237.
[11] Lee, S., Oh, S.W., Nam, K. (2016). “Transformational and transactional factors for the successful implementation of enterprise architecture in public sector”. Sustainability, 8(5), 456, doi: https://doi.org/10.3390/su8050456.
[12] Melillo, P., Pecchia, L. (2016). “What is the appropriate sample size to run analytic hierarchy process in a survey-based research”. In: Proceedings of the International Symposium on the Analytic Hierarchy Process, (pp. 4-8), doi: https://doi.org/10.13033/isahp.y2016.130.
[13] Nikpay, F., Selamat, H., Rouhani, B.D., Nikfard, F. (2013). “A review of critical success factors of enterprise architecture implementation”. International Conference on Informatics and Creative Multimedia, Kuala Lumpur, Malaysia, 38-4, doi: https://doi.org/10.1109/ICICM.2013.16.
[14] Patel, K., Shah, M., Qureshi, K.M., Qureshi, M.F.N. (2026). “A systematic review of generative AI: Importance of industry and startup-centered perspectives, agentic AI, ethical considerations challenges, and future directions. Artificial Intelligence Review, 59(7), doi: https://doi.org/10.1007/s10462-025-11435-z.
[15] Rouhani, B.D., Ahmad, R.B., Nikpay, F., Mohamaddoust, R. (2019). “Critical success factor model for enterprise architecture implementation”. Malaysian Journal of Computer Science, 32(2), 133-148, doi: https://doi.org/10.22452/mjcs.vol32no2.4.
[16] Rouhani, B.D., Mahrin, M.N.R., Nikpay, F., Nikfard, P., Najafabadi, M. K. (2015). “Factors that affect the effectiveness of enterprise architecture implementation methodology”. International Journal of Economics and Management Engineering, 9(1), 19-25, doi: https://doi.org/10.5281/ZENODO.1337678.
[17] Ranjbarfard, M., Mirsalari, S.R. (2016). “A systematic review of frameworks, benefits, metrics and key success factors of enterprise architecture”. First National Conference on Innovation in IS/IT Management with BI Approach, Tehran, https://mpra.ub.uni-muenchen.de/id/eprint/114739.
[18] Schmidt, C., Buxmann, P. (2011). “Outcomes and success factors of enterprise IT architecture management: Empirical insight from the international financial services industry”. European journal of information systems, 20(2), 168-185, doi: https://doi.org/10.1057/ejis.2010.68.
[19] Tamm, T., Seddon, P.B., Shanks, G. (2022). “How enterprise architecture leads to organizational benefits”. International Journal of Information Management, 67, 102554, doi: https://doi.org/10.1016/j.ijinfomgt.2022.102554.
[20] Vaidya, O.S., Kumar, S. (2006). “Analytic hierarchy process: An overview of applications”. European Journal of operational research, 169(1), 1-9, doi: https://doi.org/10.1016/j.ejor.2004.04.028.
[21] Van der Raadt, B., Bonnet, M., Schouten, S., Van Vliet, H. (2010). “The relation between EA effectiveness and stakeholder satisfaction”. Journal of Systems and Software, 83(10), 1954-1969, doi: https://doi.org/10.1016/j.jss.2010.05.076.
[22] Väisänen, S., Mikkilä, M., Havukainen, J., Sokka, L., Luoranen, M., Horttanainen, M. (2016). “Using a multi-method approach for decision-making about a sustainable local distributed energy system: A case study from Finland”. Journal of Cleaner Production, 137, 1330-1338, doi: https://doi.org/10.1016/j.jclepro.2016.07.173.
[23] Weill, P., Ross, W.J., Robertson, D.C. (2006). “Enterprise Architecture as Strategy”, Harvard Business School Press, Massachusetts.
[24] Wit, W. Van der Meer, J. (2010). “Enterprise architecture: The relationship between architecture and organizational change”. Proceedings of the 2010 IEEE International Conference on Management of Innovation and Technology.
[25] Ylimäki, T. (2006). “Towards critical success factors for enterprise architecture: [AISA Project report]”. Evaluation of enterprise and software architectures: Critical issues, metrics and practices/Eetu Niemi, Tanja Ylimäki & Niina Hämäläinen (eds.). Jyväskylä: University of Jyväskylä, Information Technology Research Institute, 2008. (Tietotekniikan tutkimusinstituutin julkaisuja, ISSN 1236-1615; 18). ISBN 978-951-39-3108-7 (CD-ROM).
Control and Optimization in Applied Mathematics

Articles in Press, Accepted Manuscript
Available Online from 28 December 2025
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