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Journals / Türkiye Teknoloji ve Uygulamalı Bilimler Dergisi / 2026 / Sayı: 2026

Technology Acceptance in Architecture: Systematic Literature Review of TAM and Related Models (2005-2025)

Çağatay Yaldız(YILDIZ TEKNİK ÜNİVERSİTESİ)0009-0006-6238-4902
Ilkim Markoc(YILDIZ TEKNİK ÜNİVERSİTESİ)0000-0002-7805-1153
Pages
1–15
Publication Date
2026-03-27
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

It therefore outlines a research agenda towards architecture-specific acceptance structures and, in particular, context-sensitive models for generative AI.

📌 3 Key Takeaways

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Objective & Hypothesis:As digital transformation in architecture accelerates, moving from CAD to BIM, and from parametric design to VR/AR and generative AI, the practical value of these technologies depends on adoption decisions made by users and organisations.
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Key Findings & Data:This study aims to systematically map how the Technology Acceptance Model (TAM) and related frameworks (TAM2/TAM3, UTAUT) have been applied in architecture, identify dominant themes, patterns of variables and architecture-specific determinants, and propose an agenda for future research.
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Conclusion & Impact:It therefore outlines a research agenda towards architecture-specific acceptance structures and, in particular, context-sensitive models for generative AI.
🔬Design:Review & Systematic Survey
📍Scope:2015–2025 Verileri
⚙️Variables:Teknoloji Kabul Modeli (TAM) · Mimarlık Teknolojileri · Yapı Bilgi Modellemesi (BIM)

Abstract

As digital transformation in architecture accelerates, moving from CAD to BIM, and from parametric design to VR/AR and generative AI, the practical value of these technologies depends on adoption decisions made by users and organisations. Yet technology-acceptance research in the architecture, engineering and construction context remains fragmented across different technologies, user groups and theoretical models. This study aims to systematically map how the Technology Acceptance Model (TAM) and related frameworks (TAM2/TAM3, UTAUT) have been applied in architecture, identify dominant themes, patterns of variables and architecture-specific determinants, and propose an agenda for future research. Following PRISMA principles, a two-stage systematic review was conducted covering 2015–2025. The search spanned Scopus, Web of Science, ScienceDirect, SpringerLink, Taylor & Francis Online, Emerald and MDPI. For national coverage, TR Dizin and the Council of Higher Education (YÖK) National Thesis Centre were also screened. In the first stage, 350 records were thematically classified at title and abstract level. In the second stage, 176 studies were coded by technology type, target user group, acceptance model employed, and added external variables, and were synthesised through mixed qualitative and quantitative content analysis. The findings show that the literature concentrates on professional practice and production technologies. At the same time, a rapidly expanding stream foregrounds representation, experience and stakeholder communication through VR/AR and virtual environments. Although perceived usefulness (PU) and perceived ease of use (PEOU) retain their central role, trust, social influence and facilitating conditions become more salient for technologies that require collaboration and organisational transformation. In educational settings, self-efficacy and studio-culture-specific social learning dynamics stand out. The study renders core and extended acceptance variables comparatively visible and argues that “usefulness” should be expanded beyond productivity to include design quality and creativity. It therefore outlines a research agenda towards architecture-specific acceptance structures and, in particular, context-sensitive models for generative AI.

Özet

Mimarlıkta CAD’den BIM’e, parametrik tasarımdan VR/AR ve üretken yapay zekaya uzanan dijital dönüşüm hızlanırken, bu teknolojilerin pratikte değer üretmesi kullanıcıların ve örgütlerin benimseme kararlarına bağlıdır. Ancak mimarlık-mühendislik-yapım bağlamındaki teknoloji kabulü çalışmaları farklı teknolojilere, kullanıcı gruplarına ve kuramsal modellere dağılmış durumdadır. Bu çalışma, Teknoloji Kabul Modeli (TAM) ve ilişkili çerçevelerin (TAM2/TAM3, UTAUT) mimarlık alanında nasıl kullanıldığını sistematik biçimde haritalamak; baskın temaları, değişken örüntülerini ve mimarlığa özgü belirleyicileri ortaya koyarak gelecek araştırmalar için bir gündem önermeyi amaçlamaktadır. PRISMA ilkeleri izlenerek 2015-2025 dönemini kapsayan iki aşamalı sistematik tarama yürütülmüştür: Scopus, Web of Science, ScienceDirect, SpringerLink, Taylor & Francis Online, Emerald ve MDPI; ulusal kapsam için TR Dizin ve YÖK Ulusal Tez Merkezi taranmıştır. İlk aşamada 350 kayıt başlık-özet düzeyinde tematik sınıflandırılmış; ikinci aşamada 176 çalışma teknoloji türü, hedef kullanıcı grubu, kullanılan kabul modeli ve eklenen dışsal değişkenler üzerinden kodlanarak nitel-nicel içerik analiziyle sentezlenmiştir. Bulgular, literatürün mesleki pratik/üretim teknolojilerinde yoğunlaştığını; VR/AR ve sanal ortamlar üzerinden temsil, deneyim ve paydaş iletişimini öne çıkaran hızla büyüyen bir hattın oluştuğunu göstermektedir. PU ve PEOU merkezi rolünü korurken, işbirliğine dayalı ve örgütsel dönüşüm gerektiren teknolojilerde güven, sosyal etki ve kolaylaştırıcı koşullar belirginleşmektedir; eğitim bağlamında öz-yeterlilik ve stüdyo kültürüne özgü sosyal öğrenme dinamikleri öne çıkmaktadır. Çalışma, çekirdek ve genişletilmiş kabul değişkenlerini karşılaştırmalı görünür kılar; faydanın verimlilikle sınırlanmayıp tasarım kalitesi/yaratıcılık boyutlarıyla genişletilmesi gerektiğini vurgulayarak, mimarlığa özgü kabul yapıları ve özellikle üretken yapay zeka için bağlam-duyarlı modeller yönünde bir araştırma gündemi sunar.

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Cite This Article

Yaldız, Ç., Markoc, I. (2026). Technology Acceptance in Architecture: Systematic Literature Review of TAM and Related Models (2005-2025). Türkiye Teknoloji ve Uygulamalı Bilimler Dergisi, Sayı: 2026, 1–15. https://doi.org/10.70562/tubid.1851239

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References (42)

  1. Adeniyi, O. and Thurairajah, N. (2024) Rethinking digital construction: Bim uptake. Construction Innovation, 24, 584–605.
  2. Ahmed, A. L. and Kassem, M. (2018) A unified bim adoption taxonomy: Conceptual development, empirical validation and application. Automation in Construction, 96, 103–127.
  3. Algassim, H., Sepasgozar, S. M. E., Ostwald, M. and Davis, S. (2023) A qualitative study on factors influencing technology adoption in the architecture industry. Buildings, 13, 1100.
  4. Alghamdi, S., Tang, W. C., Kanjanabootra, S. and Alterman, D. (2023) Optimal configuration of architectural building design parameters for higher educational buildings. Energy Reports, 10, 1925–1942.
  5. Alonso, R., Locci, R. and Reforgiato Recupero, D. (2024) Improving digital twin experience through big data, iot and social analysis: An architecture and a case study. Heliyon, 10, e24741.
  6. Avsar, A. Z., Chiesi, S. and Grogan, P. T. (2022) Effects of data exchange methods on perceived risk and trust in digital engineering. 29th International Society of Transdisciplinarity Engineering (ISTE) Global Conference, Cambridge, MA, USA. IOS Press, 249–258.
  7. Barosio, M., Vigliocco, E. and Gomes, S. eds., 2024. School of Architecture (s)-New Frontiers of Architectural Education: EAAE Annual Conference—Turin 2023. Springer Nature.
  8. Chen, X., Chang-Richards, A., Ling, F. Y. Y., Yiu, T. W., Pelosi, A. and Yang, N. (2023) Developing a readiness model and a self-assessment tool for adopting digital technologies in construction organizations. Building Research & Information, 51, 241–256.
  9. Cui, Q. H., Hu, X. C., Liu, X., Zhao, L. M. and Wang, G. B. (2021) Understanding architectural designers' continuous use intention regarding bim technology: A china case. Buildings, 11, 403.
  10. Davis, F. D. (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13, 319–340.
  11. Deshapriya, L. a. M., Perera, B. a. K. S., Ilangakoon, I. W. M. a. D. and Weerasooriya, D. (2025) Management of adverse effects of construction digitalization on the quantity surveying key roles: A qualitative delphi study. Journal of Engineering Design and Technology, 23, 1815–1837.
  12. Elkhayat, Y., Adel, K. and Marzouk, M. (2024) Technology adoption in the construction industry (1999-2023): Science mapping and visualization. Automation in Construction, 165, 105287.
  13. Heo, S. and Na, S. (2025) Ready for departure: Factors to adopt large language model (llm)-based artificial intelligence (ai) technology in the architecture, engineering and construction (aec) industry. Results in Engineering, 25, 103456.
  14. Ibrahim, K. and Okanlawon, T. T. (2024) Construction 4.0: Digital twin barriers in nigeria. ECAM, 31, 1532–1555. Kitchenham, B. and Charters, S., 2007. Guidelines for performing systematic literature reviews in software engineering. Technical Report EBSE 2007-001. Keele University and Durham University.
  15. Klein, H. C., Stelter, A., Oschinsky, F. M. and Niehaves, B. (2022) A status quo bias perspective on user resistance in building information modeling adoption–towards a taxonomy. Computers in Industry, 143, 103760.
  16. Köse, I. and Gümüşburun Ayalp, G. (2024) Transformative impacts of technological developments on architectural education. Engineering, Construction and Architectural Management, 31, 4050–4074.
  17. Lee, J. G., Seo, J., Abbas, A. and Choi, M. (2020) End-users' augmented reality utilization for architectural design review. Applied Sciences-Basel, 10, 5174.
  18. Lin, C. Y. and Xu, N. (2022) Extended tam model for ai robotic architects. Tech. Anal. Strat. Manage., 34, 303–316.
  19. Lin, M. and Huang, Y., 2023, July. Research on user experience design strategy of digital aquarium based on UTAUT2 model. In International Conference on Human-Computer Interaction (pp. 167-188). Cham: Springer Nature Switzerland.
  20. Liu, Y. and Konduri, S. (2024) Vr systems for building evaluation. Buildings, 14, 3714.
  21. Manzoor, B., Othman, I. and Pomares, J. C. (2021) Digital technologies in the architecture, engineering and construction (aec) industry-a bibliometric-qualitative literature review of research activities. International Journal of Environmental Research and Public Health, 18, 6135.
  22. Mata, M., Ancheta, R., Batucan, G. and Gonzales, G.G., 2024. Exploring technology acceptance model with system characteristics to investigate sustainable building information modeling adoption in the architecture, engineering, and construction industry: The case of the Philippines. Social Sciences & Humanities Open, 10, p.100967.
  23. Moher, D. and Liberati, A. (2009) The prisma statement. PLoS Medicine, 6, e1000097.
  24. Murguia, D., Demian, P. and Soetanto, R. (2021) Systemic bim adoption: A multilevel perspective. Journal of Construction Engineering and Management, 147.
  25. Okoro, C. S., Nnaji, C. and Adediran, A. (2022) Determinants of immersive technology acceptance in the construction industry: Management perspective. Engineering, Construction and Architectural Management, 30, 2645-2668.
  26. Olanrewaju, O. I., Kineber, A. F., Chileshe, N. and Edwards, D. J. (2022) Modelling the relationship between building information modelling (bim) implementation barriers, usage and awareness on building project lifecycle. Building and Environment, 207, 108556.
  27. Özgen, D. S., Afacan, Y. and Sürer, E. (2021) Usability of virtual reality for design education. International Journal of Technology and Design Education, 31, 895–915.
  28. Özkaynar, K., 2024. Teknoloji kabul modeli çerçevesinde, tüketicilerin yapay zekâ araçlarını kullanımlarında algılanan fayda, tutum ve niyetler arasındaki ilişki: etik kaygıların düzenleyici etkisi. Yönetim Bilimleri Dergisi, 22(Özel Sayı: Endüstri 4.0 ve Dijitalleşmenin Sosyal Bilimlerde Yansımaları), pp.1472-1498.
  29. Picon, A., 2010. Digital culture in architecture: An introduction for the design professions. In Digital Culture in Architecture. Birkhäuser.
  30. Purup, P. B. and Petersen, S. (2020) Research framework for development of building performance simulation tools for early design stages. Automation in Construction, 109, 103168.
  31. Santos, V. and Soares, M. S. (2023) Design and evaluation using technology acceptance model of an architecture conceptualization framework system based on the iso/iec/ieee 42020. Journal of Universal Computer Science, 29, 1510–1534.
  32. Sepasgozar, S. M. E. (2022) Immersive training and modified tam. Technology in Society, 68, 101921.
  33. Sepasgozar, S.M., Ghobadi, M., Shirowzhan, S., Edwards, D.J. and Delzendeh, E., 2021. Metrics development and modelling the mixed reality and digital twin adoption in the context of Industry 4.0. Engineering, Construction and Architectural Management, 28(5), pp.1355-1376.
  34. Soulikias, A., Cucuzzella, C. and Nizar, F. (2021) Critical reflection on digital design technologies. Open House International, 46, 444–458.
  35. Ullah, K., Witt, E. and Lill, I., 2023. BIM Adoption Processes: Findings from a Systematic Literature Review. In Nordic Conference on Construction Economics and Organization (pp. 223-236). Springer, Cham.
  36. Venkatesh, V. and Bala, H. (2008) Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39, 273–315.
  37. Venkatesh, V. and Davis, F. D. (2000) A theoretical extension of the tam. Management Science, 46, 186–204.
  38. Venkatesh, V., Morris, M. G. and Davis, G. B. (2003) User acceptance of it: Toward a unified view. MIS Quarterly, 27, 425–478.
  39. Wang, K. Y., Guo, F. Y., Zhang, C. and Schaefer, D. (2024) From industry 4.0 to construction 4.0: Barriers to the digital transformation of engineering and construction sectors. Engineering Construction and Architectural Management, 31, 136–158.
  40. Wei, W., Prasetyo, Y. T., Belmonte, Z. J. A., Cahigas, M. M. L., Nadlifatin, R. and Gumasing, M. J. J. (2025) Applying the technology acceptance model - theory of planned behavior (tam-tpb) model to study the acceptance of building information modeling (bim) in green building in china. Acta Psychol (Amst), 254, 104790.
  41. Wu, W. and Zhao, Z. (2022) Immersive vr in landscape education. Sustainability, 14, 16891.
  42. Zhang, M., Shu, L., Luo, X., Yuan, M. and Zheng, X. (2022) Virtual reality technology in construction safety training: Extended technology acceptance model. Automation in Construction, 135, 104113.