Development of a DEMATEL-ANP Model for Analyzing Determinants of Artificial Intelligence Adoption Intention among SMEs

Dutho Suh Utomo, Ridzky Zul Asdi, La Ode Ahmad Safar Tosungku

Abstract


Artificial Intelligence (AI) adoption provides significant opportunities for Small and Medium Enterprises (SMEs) to improve operational efficiency, decision-making, and competitiveness. However, SMEs still face various challenges in adopting AI technologies, including limited financial resources, digital capability, technological readiness, and organizational preparedness. This study aims to develop a DEMATEL-ANP model to identify causal relationships and prioritize determinants influencing AI adoption intention among SMEs. A quantitative approach using Multi-Criteria Decision-Making (MCDM) was applied by integrating the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Analytic Network Process (ANP) methods. The proposed model incorporates technological, organizational, and environmental factors based on the Technology Acceptance Model (TAM) and Technology-Organization-Environment (TOE) framework. Data were collected through expert judgment from five experts with knowledge and experience in artificial intelligence, digital transformation, SME development, and technology adoption. The DEMATEL results indicate that all evaluated factors belong to the cause group, with Digital Capability (DC) identified as the most influential factor. Furthermore, ANP results reveal that Cost (0.15) and Digital Capability (0.15) are the highest priority factors, followed by Competitive Pressure (0.14) and Perceived Usefulness (0.13). The consistency evaluation confirms that all ANP comparison matrices meet the consistency requirement with a Consistency Ratio below 0.10. This study contributes by providing a comprehensive decision-making framework for understanding AI adoption determinants among SMEs and identifying key factors that should be prioritized to support successful AI implementation


Keywords


Artificial Intelligence Adoption; SMEs; DEMATEL; ANP; Technology Adoption

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Ahmad, K., Islam, M. S., Jahin, M. A., & Mridha, M. F. (2024). Analysis of Internet of things implementation barriers in the cold supply chain: An integrated ISM-MICMAC and DEMATEL approach. Plos One, 19(7), e0304118.

Awa, H. O., Ukoha, O., & Igwe, S. R. (2017). Revisiting technology-organization-environment (TOE) theory for enriched applicability. The Bottom Line, 30(1), 2–22.

Ayinaddis, S. G. (2025). Artificial intelligence adoption dynamics and knowledge in SMEs and large firms: A systematic review and bibliometric analysis. Journal of Innovation & Knowledge, 10(3), 100682.

Badghish, S., & Soomro, Y. A. (2024). Artificial intelligence adoption by SMEs to achieve sustainable business performance: application of technology–organization–environment framework. Sustainability, 16(5), 1864.

Büyüközkan, G., Güleryüz, S., & Karpak, B. (2017). A new combined IF-DEMATEL and IF-ANP approach for CRM partner evaluation. International Journal of Production Economics, 191, 194–206.

Chatterjee, S., Chaudhuri, R., Vrontis, D., & Basile, G. (2022). Digital transformation and entrepreneurship process in SMEs of India: a moderating role of adoption of AI-CRM capability and strategic planning. Journal of Strategy and Management, 15(3), 416–433

.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 319–340.

Del Giudice, M., Scuotto, V., Papa, A., Tarba, S. Y., Bresciani, S., & Warkentin, M. (2021). A self‐tuning model for smart manufacturing SMEs: Effects on digital innovation. Journal of Product Innovation Management, 38(1), 68–89.

DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: a ten-year update. Journal of Management Information Systems, 19(4), 9–30.

Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., & Eirug, A. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994.

Enholm, I. M., Papagiannidis, E., Mikalef, P., & Krogstie, J. (2022). Artificial intelligence and business value: A literature review. Information Systems Frontiers, 24(5), 1709–1734.

Gabus, A., & Fontela, E. (1972). World Problems, an Invitation to Further Thought within the Framework of DEMATEL. Battelle Geneva Research Center, 1(8), 12–14.

Govindan, K., & Chaudhuri, A. (2016). Interrelationships of risks faced by third party logistics service providers: A DEMATEL based approach. Transportation Research Part E: Logistics and Transportation Review, 90, 177–195.

Hasani, T., Rezania, D., & Mohammadi, M. H. (2024). Towards a framework for successful metaverse adoption in Small and Medium-sized Enterprises: An exploratory study. International Journal of Engineering Business Management, 16. https://doi.org/10.1177/18479790241257118

Hussain, A., & Rizwan, R. (2024). Strategic AI adoption in SMEs: A prescriptive framework. ArXiv Preprint ArXiv:2408.11825.

Jöhnk, J., Weißert, M., & Wyrtki, K. (2021). Ready or Not, AI Comes—An Interview Study of Organizational AI Readiness Factors: J. Jöhnk et al.: Ready or Not, AI Comes: An Interview Study of Organizational AI Readiness Factors. Business & Information Systems Engineering, 63(1), 5–20.

Khin, S., & Ho, T. C. F. (2019). Digital technology, d igital capability, and organizational performan ce. International Journal of Innovation, Creativ Ity and Change, 8(1), 1–14.

Kraus, S., Jones, P., Kailer, N., Weinmann, A., Chaparro-Banegas, N., & Roig-Tierno, N. (2021). Digital transformation: An overview of the current state of the art of research. Sage Open, 11(3), 21582440211047576.

Lee, W.-S., Huang, A. Y., Chang, Y.-Y., & Cheng, C.-M. (2011). Analysis of decision making factors for equity investment by DEMATEL and Analytic Network Process. Expert Systems with Applications, 38(7), 8375–8383.

Lokuge, S., & Duan, S. X. (2021). Towards understanding enablers of digital transformation in small and medium-sized enterprises. ArXiv Preprint ArXiv:2111.05989.

Mariani, M. M., Perez‐Vega, R., & Wirtz, J. (2022). AI in marketing, consumer research and psychology: A systematic literature review and research agenda. Psychology & Marketing, 39(4), 755–776.

Mikalef, P., & Gupta, M. (2021). Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance. Information & Management, 58(3), 103434.

Ocampo, L. A., Himang, C. M., Kumar, A., & Brezocnik, M. (2019). A novel multiple criteria decision-making approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy AHP for mapping collection and distribution centers in reverse logistics. Advances in Production Engineering & Management, 14(3).

Rogers, E. (2003). M. Diffusion of innovations. New York: The Free.

Saaty, T. L. (1996). Decisions with the analytic network process (ANP). University of Pittsburgh (USA), ISAHP, 96.

Saaty, T. L. (2005). Theory and applications of the analytic network process: decision making with benefits, opportunities, costs, and risks. RWS publications.

Saaty, T. L., & Vargas, L. G. (2013). The analytic network process. In Decision making with the analytic network process: Economic, political, social and technological applications with benefits, opportunities, costs and risks (pp. 1–40). Springer.

Sánchez, E., Calderón, R., & Herrera, F. (2025). Artificial intelligence adoption in SMEs: Survey based on TOE–DOI framework, primary methodology and challenges. Applied Sciences, 15(12), 6465.

Sánchez-Rodríguez, A., García-Vidal, G., Fernández-Ochoa, Y., Martínez-Vivar, R., Gavilanes-Venegas, A. E., & Pérez-Campdesuñer, R. (2025). Navigating Uncertainty Through AI Adoption: Dynamic Capabilities, Strategic Innovation Performance, and Competitiveness in Ecuadorian SMEs. Administrative Sciences, 15(12), 468. https://doi.org/10.3390/admsci15120468

Sharma, S., Singh, G., Islam, N., & Dhir, A. (2024). Why Do SMEs Adopt Artificial Intelligence-Based Chatbots? Ieee Transactions on Engineering Management, 71, 1773–1786. https://doi.org/10.1109/tem.2022.3203469

Shieh, J.-I., Wu, H.-H., & Huang, K.-K. (2010). A DEMATEL method in identifying key success factors of hospital service quality. Knowledge-Based Systems, 23(3), 277–282.

Si, S.-L., You, X.-Y., Liu, H.-C., & Zhang, P. (2018). DEMATEL technique: a systematic review of the state‐of‐the‐art literature on methodologies and applications. Mathematical Problems in Engineering, 2018(1), 3696457.

Thomas, G. B., Albishri, N., Islam, J. U., & Tanveer, M. (2025). Exploring the determinants of Artificial Intelligence adoption intention in the SMEs of United Arab Emirates. Sage Open, 15(4). https://doi.org/10.1177/21582440251395561

Tornatzky, L. G. (1990). Technology-Organization Environment (TOE) Framewor k-Tornatzky & Fleischer (1990).

Utomo, D. S., & Asdi, R. Z. (2025). Pengambilan Keputusan Pemilihan Supplier Tepung untuk UMKM Roti Menggunakan Metode Multikriteria ANP-TOPSIS. Jurnal Rekayasa Industri (JRI), 7(2), 132–140.

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view1. MIS Quarterly, 27(3), 425–478.

Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A., Dong, J. Q., Fabian, N., & Haenlein, M. (2021). Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research, 122, 889–901.

Vrontis, D., Christofi, M., Pereira, V., Tarba, S., Makrides, A., & Trichina, E. (2023). Artificial intelligence, robotics, advanced technologies and human resource management: a systematic review. Artificial Intelligence and International HRM, 172–201.




DOI: https://doi.org/10.53889/citj.v4i2.958

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