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<p>Innovative façade systems and artificial intelligence (AI)–enabled building technologies are increasingly central to sustainable construction, yet their adoption in emerging markets depends heavily on customer awareness and perceived usefulness. This study examines awareness, perceptions, and adoption intention for these technologies among key stakeholders in Chennai’s construction sector. Grounded in an integrated Technology Acceptance Model (TAM) and Diffusion of Innovation (DOI) framework, the study employs a mixed-methods design comprising a structured survey of 250 respondents and thematic analysis of open-ended responses. Quantitative analysis using SPSS included descriptive statistics, correlation tests, and multiple regression modelling. Results indicate limited awareness of advanced façade systems but moderate familiarity with AI-based building management applications. Awareness significantly predicts adoption intention (β = 0.55, <i>p</i> &lt; 0.001), highlighting the role of informational exposure in shaping acceptance. Qualitative findings further reveal cost perceptions, technological complexity, and trust concerns as influencing factors. The study contributes theoretically by extending TAM–DOI integration to dual-technology building innovations and provides practical insights for manufacturers, developers, and policymakers seeking to accelerate smart-building transformation in Indian cities. </p>

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Understanding customer awareness of innovative façade products and AI technologies in Chennai’s construction sector

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月4日

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  • K. Rajaprabakaran,
  • A. Geetha

摘要

Innovative façade systems and artificial intelligence (AI)–enabled building technologies are increasingly central to sustainable construction, yet their adoption in emerging markets depends heavily on customer awareness and perceived usefulness. This study examines awareness, perceptions, and adoption intention for these technologies among key stakeholders in Chennai’s construction sector. Grounded in an integrated Technology Acceptance Model (TAM) and Diffusion of Innovation (DOI) framework, the study employs a mixed-methods design comprising a structured survey of 250 respondents and thematic analysis of open-ended responses. Quantitative analysis using SPSS included descriptive statistics, correlation tests, and multiple regression modelling. Results indicate limited awareness of advanced façade systems but moderate familiarity with AI-based building management applications. Awareness significantly predicts adoption intention (β = 0.55, p < 0.001), highlighting the role of informational exposure in shaping acceptance. Qualitative findings further reveal cost perceptions, technological complexity, and trust concerns as influencing factors. The study contributes theoretically by extending TAM–DOI integration to dual-technology building innovations and provides practical insights for manufacturers, developers, and policymakers seeking to accelerate smart-building transformation in Indian cities.