Palabras clave
Consumer Buying Behavior
Smart Waste Management
Sustainable Development Goals
Indian Real Estate
Cómo citar
Resumen
Objective: This study aimed to investigate the impact of Smart Building Technology (SBT) on Customer Buying Behaviour (CBB) in the Indian real estate sector. The research addresses the problem of limited understanding of how emerging smart technologies influence consumer decision-making in real estate purchases. It further sought to identify key smart technology factors influencing purchasing decisions and to examine their contribution to sustainable development goals, particularly SDG-13 (climate action).
Methodology/Approach: A structured questionnaire was developed and distributed among 232 respondents, including customers, architects, developers, and real estate company staff. Data were analysed using SPSS-25 and AMOS. Factor analysis identified five critical components of SBT, while Structural Equation Modelling (SEM) was employed to test hypotheses and evaluate the influence of these factors on consumer behaviour.
Originality/Relevance: This research provided original insights into how smart building components contribute not only to enhancing customer satisfaction but also to achieving environmental sustainability goals. The relevance lies in addressing the growing demand for climate-conscious infrastructure solutions in the Indian real estate market.
Main Conclusion: Among the five identified factors—Smart Security System, Building Automation System, Information Technology Services, Smart Waste Management, and Smart Water Management—Building Automation and Smart Security emerged as the most influential determinants of consumer satisfaction. SEM results confirmed a significant and positive influence of SBT on CBB (β = 0.56, p = 0.000), validating hypotheses H1, H4, and H6.
Theoretical/Methodological Contributions: The study contributed to the existing literature by integrating environmental sustainability with consumer behavior in smart infrastructure adoption. Methodologically, it validates a conceptual framework through robust statistical techniques, offering a scalable model for future research in technology-enabled sustainable real estate development.
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