Multi-criteria decision analysis of e-commerce software selection using AHP-NWA hybrid model

DOI: https://doi.org/10.3846/jbem.2026.25406

Abstract

In the digital economy, selecting the right e-commerce platform is a strategic decision with significant implications for efficiency and competitiveness. This paper applies a hybrid decision-making framework that integrates the Analytic Hierarchy Process (AHP) and Net Worth Analysis (NWA) to evaluate five popular e-commerce platforms: Magento, WooCommerce, Shopify, PrestaShop, and OpenCart. AHP was used to derive weights for evaluation criteria, while NWA incorporated expert assessments of alternatives. Results indicate that security (32%) and functionality (25%) are the most critical factors, followed by maintenance costs (14%) and scalability (11%). The ranking shows Magento as the leading platform (0.575), excelling in security and functionality, while WooCommerce (0.567) is highly flexible and Shopify (0.563) stable though less customizable. PrestaShop (0.505) and OpenCart (0.496) scored lower, making them suitable for smaller businesses. The contribution of this study lies in the integration of AHP-derived weights into the NWA framework under a dual expert panel structure, ensuring methodological independence and reducing bias. This hybrid approach offers both practical implications for digital business strategy and theoretical insights into combining hierarchical and network-based MCDM methods, thereby addressing a research gap in e-commerce software evaluation.

Keywords:

e-commerce, multi-criteria decision-making, AHP, NWA, software platforms, Magento, WooCommerce, Shopify

How to Cite

Rakić, R., Gligorijević, M., Viduka, D., Gligorijević, N., & Strugarević, D. (2026). Multi-criteria decision analysis of e-commerce software selection using AHP-NWA hybrid model. Journal of Business Economics and Management, 27(1), 38–57. https://doi.org/10.3846/jbem.2026.25406

Share

Published in Issue
January 23, 2026
Abstract Views
71

References

Abdallah, A. B., Phan, A. C., & Matsui, Y. (2016). Investigating the effects of managerial and technological innovations on operational performance and customer satisfaction of manufacturing companies. International Journal of Business Innovation and Research, 10(2–3), 153–183. https://doi.org/10.1504/IJBIR.2016.074824

Aitazaz, F. (2023). Advanced AI/ML techniques for business intelligence in IoT-enabled manufacturing with ERP cloud integration. https://www.researchgate.net/publication/388802376_Advanced_AIML_Techniques_for_Business_Intelligence_in_IoT-_Enabled_Manufacturing_with_ERP_Cloud_Integration

Ajiga, D., Okele, P. A., Folorunsho, S. A., & Ezeigweneme, O. (2024). Methodologies for developing scalable software frameworks that support growing business needs. International Journal of Management and Entrepreneurship Research, 6, 2661–2683. https://doi.org/10.51594/ijmer.v6i8.1413

Albayrak, E., & Erensal, Y. C. (2004). Using analytic hierarchy process (AHP) to improve human performance: An application of multiple criteria decision making problem. Journal of Intelligent Manufacturing, 15, 491–503. https://doi.org/10.1023/B:JIMS.0000034112.00652.4c

Aruldoss, M., Lakshmi, T. M., & Venkatesan, V. P. (2013). A survey on multi criteria decision making methods and its applications. American Journal of Information Systems, 1(1), 31–43.

Ayan, B., Abacıoğlu, S., & Basilio, M. P. (2023). A comprehensive review of the novel weighting methods for multi-criteria decision-making. Information, 14(5), Article 285. https://doi.org/10.3390/info14050285

Baršauskas, P., Šarapovas, T., & Cvilikas, A. (2008). The evaluation of e‐commerce impact on business efficiency. Baltic Journal of Management, 3(1), 71–91. https://doi.org/10.1108/17465260810844275

Bediako, G. (2023). The application of Big Data Analytics in improving eCommerce processes. The Retail sector user experience [BSc thesis, Häme University of Applied Sciences].

Beynon, M. (2002). An analysis of distributions of priority values from alternative comparison scales within AHP. European Journal of Operational Research, 140(1), 104–117. https://doi.org/10.1016/S0377-2217(01)00221-1

Bilgihan, A., Kandampully, J., & Zhang, T. (2016). Towards a unified customer experience in online shopping environments: Antecedents and outcomes. International Journal of Quality and Service Sciences, 8(1), 102–119. https://doi.org/10.1108/IJQSS-07-2015-0054

Bonissone, P. P., Subbu, R., & Lizzi, J. (2009). Multicriteria decision making (MCDM): A framework for research and applications. IEEE Computational Intelligence Magazine, 4(3), 48–61. https://doi.org/10.1109/MCI.2009.933093

Chillapalli, N. T. R. (2022). Software as a service (SaaS) in e-commerce: The impact of cloud computing on business agility. Journal of Engineering and Computer Sciences, 1(10), 7–18.

Daniele, C. (2025, March 19). Performance requirements and 10 best practices for high-speed e-commerce websites. Kinsta. https://kinsta.com/blog/ecommerce-performance/

Ehikioya, S. A., & Guillemot, E. (2020). A critical assessment of the design issues in e‐commerce systems development. Engineering Reports, 2(4), Article e12154. https://doi.org/10.1002/eng2.12155

Erevelles, S., Fukawa, N., & Swayne, L. (2016). Big Data consumer analytics and the transformation of marketing. Journal of Business Research, 69(2), 897–904. https://doi.org/10.1016/j.jbusres.2015.07.001

Ernst & Young. (2021, March 18). Three things to consider when evaluating your e-commerce platform. EY. https://www.ey.com/en_gl/alliances/three-things-to-consider-when-evaluating-your-e-commerce-platform

Fraccastoro, S., Gabrielsson, M., & Pullins, E. B. (2021). The integrated use of social media, digital, and traditional communication tools in the B2B sales process of international SMEs. International Business Review, 30(4), Article 101776. https://doi.org/10.1016/j.ibusrev.2020.101776

Gregory, R., Failing, L., Harstone, M., Long, G., McDaniels, T., & Ohlson, D. (2012). Structured decision making: A practical guide to environmental management choices. John Wiley & Sons. https://doi.org/10.1002/9781444398557

Hazra, R., Chatterjee, P., Singh, Y., Podder, G., & Das, T. (2024). Data encryption and secure communication protocols. In P. K. Goel (Ed.), Strategies for e-commerce data security: Cloud, blockchain, AI, and machine learning (pp. 546–570). IGI Global. https://doi.org/10.4018/979-8-3693-6557-1.ch022

IronPlane. (2023, May 15). Understanding the true cost of eCommerce platform support and maintenance. IronPlane. https://www.ironplane.com/ironplane-ecommerce-blog/understanding-the-true-cost-of-ecommerce-platform-support-and-maintenance

Jayathilaka, R., & Udara, I. (2024). Security matters: Empowering e-commerce in Sri Lanka through customer insights. Humanities and Social Sciences Communications, 11, Article 1054. https://doi.org/10.1057/s41599-024-03585-2

Karamchand, G. K. (2024). Scaling new heights: The role of cloud computing in business transformation. International Journal of Digital Innovation, 5(1).

Karim, R. A., Rabiul, M. K., Tahrin, S., & Arfat, S. M. (2024). The nexus between CRM and behavioural loyalty

in hotel sector: The mediating role of relationship quality (trust and satisfaction). Global Knowledge, Memory and Communication. https://doi.org/10.1108/GKMC-03-2024-0169

Khurana, R. (2020). Fraud detection in ecommerce payment systems: The role of predictive AI in real-time transaction security and risk management. International Journal of Applied Machine Learning and Computational Intelligence, 10(6), 1–32.

Lakshmi, P., StalinDavid, D., Kalaria, H. I., Jayadatta, S., Sharma, A., & Saravanan, D. (2020). Research on collaborative innovation of E-commerce business model for commercial transactions. Turkish Journal of Physiotherapy and Rehabilitation, 32(3), 787–794.

Lee, C.-S. (2001). An analytical framework for evaluating e‐commerce business models and strategies. Internet Research, 11(4), 349–359. https://doi.org/10.1108/10662240110402803

Li, C., Ke, J., & Cai, L. (2024). Application research of factor constraint algorithm in E-commerce logistics route optimization. Decision Making: Applications in Management and Engineering, 7(1), 145–159. https://doi.org/10.31181/dmame712024932

Lichon, J. (2023, June 27). 14 key factors in selecting the best commerce software. BlueBolt Solutions. https://www.blueboltsolutions.com/14-key-factors-in-selecting-the-best-commerce-software/

Lu, Y. (2019). Artificial intelligence: A survey on evolution, models, applications and future trends. Journal of Management Analytics, 6(1), 1–29. https://doi.org/10.1080/23270012.2019.1570365

Lu, Y.-H., Yeh, C.-C., & Liau, T.-W. (2023). Exploring the key factors affecting the usage intention for cross-border e-commerce platforms based on DEMATEL and EDAS method. Electronic Commerce Research, 23(4), 2517–2539. https://doi.org/10.1007/s10660-022-09548-6

Marinović, M., Viduka, D., Lavrnić, I., Stojčetović, B., Skulić, A., Bašić, A., Balaban, P., & Rastovac, D. (2025). An intelligent multi-criteria decision approach for selecting the optimal operating system for educational environments. Electronics, 14(3), Article 514. https://doi.org/10.3390/electronics14030514

Martinez, M., de Andrés, D., Ruiz, J.-C., & Friginal, J. (2014). From measures to conclusions using analytic hierarchy process in dependability benchmarking. IEEE Transactions on Instrumentation and Measurement, 63(11), 2548–2556. https://doi.org/10.1109/TIM.2014.2348632

Mahmudova, S., & Jabrailova, Z. (2020). Development of an algorithm using the AHP method for selecting software according to its functionality. Soft Computing, 24, 8495–8502. https://doi.org/10.1007/s00500-020-04902-y

Miller, T. (2025, June 13). Top 10 ERP selection criteria (including checklist). ERP Focus. https://www.erpfocus.com/ten-essential-erp-selection-criteria-2640.html

Munier, N., & Hontoria, E. (2021). The hierarchical structure. In Uses and limitations of the AHP method: A non-mathematical and rational analysis (pp. 5–13). Springer. https://doi.org/10.1007/978-3-030-60392-2_2

Owusu-Berko, L. (2025). Advanced supply chain analytics: Leveraging digital twins, IoT and blockchain for resilient, data-driven business operations. World Journal of Advanced Research and Reviews, 25(2), 1777–1799. https://doi.org/10.30574/wjarr.2025.25.2.0572

Purnomo, Y. J. (2023). Digital marketing strategy to increase sales conversion on e-commerce platforms. Journal of Contemporary Administration and Management (ADMAN), 1(2), 54–62. https://doi.org/10.61100/adman.v1i2.23

Rane, N., Choudhary, S., & Rane, J. (2024, May 27). Artificial intelligence and machine learning in business intelligence, finance, and e-commerce: A review. SSRN. https://doi.org/10.2139/ssrn.4843988

Ritter, T., & Pedersen, C. L. (2020). Digitization capability and the digitalization of business models in business-to-business firms: Past, present, and future. Industrial Marketing Management, 86, 180–190. https://doi.org/10.1016/j.indmarman.2019.11.019

Rohn, D., Bican, P. M., Brem, A., Kraus, S., & Clauss, T. (2021). Digital platform-based business models – An exploration of critical success factors. Journal of Engineering and Technology Management, 60, Article 101625. https://doi.org/10.1016/j.jengtecman.2021.101625

Rosário, A., & Raimundo, R. (2021). Consumer marketing strategy and E-commerce in the last decade: A literature review. Journal of Theoretical and Applied Electronic Commerce Research, 16(7), 3003–3024. https://doi.org/10.3390/jtaer16070164

Saleem, H., Shaiq Uddin, M. K., Habib-ur-Rehman, S., Saleem, S., & Muhammad Aslam, A. (2019). Strategic data driven approach to improve conversion rates and sales performance of e-commerce websites. International Journal of Scientific & Engineering Research, 10(4), 588–593.

Saket, S., Agarwal, M., & Mehrotra, R. (2024). Crafting tomorrow: The influence of design choices on fresh content in social media recommendation. arXiv:2410.15174.

Sanbella, L., Van Versie, I., & Audiah, S. (2024). Online marketing strategy optimization to increase sales and e-commerce development: An integrated approach in the digital age. Startupreneur Business Digital (SABDA Journal), 3(1), 54–66. https://doi.org/10.33050/sabda.v3i1.492

Sheth, R., Parekha, C., Kumar, P., Kumar, A., & Patel, K. (2025). Transforming service sectors with IoT, ML, and comprehensive security solutions. In A. Kumar, P. Kumar, S. Rathee, & B. Kumar (Eds.), Mechatronics: Concepts, tools, applications, and new trends. CRC Press. https://doi.org/10.1201/9781003494478-3

Taherdoost, H., & Madanchian, M. (2023). Multi-criteria decision making (MCDM) methods and concepts. Encyclopedia, 3(1), 77–87. https://doi.org/10.3390/encyclopedia3010006

Tarafdar, M., & Vaidya, S. D. (2006). Challenges in the adoption of E-Commerce technologies in India: The role of organizational factors. International Journal of Information Management, 26(6), 428–441. https://doi.org/10.1016/j.ijinfomgt.2006.08.001

Wang, W., Sadjadi, S. M., & Rishe, N. (2024, May). A survey of major cybersecurity compliance frameworks. In 2024 IEEE 10th Conference on Big Data Security on Cloud (BigDataSecurity) (pp. 23–34). IEEE. https://doi.org/10.1109/BigDataSecurity62737.2024.00013

Zbąski, J. (2024, June 26). Scalability and flexibility in e-commerce: Handling traffic spikes and maintaining user experience. Rigby Blog. https://www.rigbyjs.com/blog/ecommerce-scalability-and-flexibility

View article in other formats

CrossMark check

CrossMark logo

Published

2026-01-23

Issue

Section

Articles

How to Cite

Rakić, R., Gligorijević, M., Viduka, D., Gligorijević, N., & Strugarević, D. (2026). Multi-criteria decision analysis of e-commerce software selection using AHP-NWA hybrid model. Journal of Business Economics and Management, 27(1), 38–57. https://doi.org/10.3846/jbem.2026.25406

Share