Raw Data Survey Sht

This dataset supports a quantitative study that investigates how social influence impacts customer behavior in adopting smart home technology in Indonesia, mediated by artificial intelligence (AI) perception and user acceptance. The research employs Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze the relationships among the four core constructs: Social Influence, User Acceptance, Artificial Intelligence Perception, and Customer Behaviour.

The data were collected via an online questionnaire distributed across various regions in Indonesia using purposive sampling. A total of 401 valid responses were obtained from individuals with prior experience using smart home technology. Each item in the instrument was measured using a nine-point Likert scale, capturing user attitudes and behavioral patterns.

Indicators include variables related to:

Social Influence (e.g., peer recommendations, community support),
User Acceptance (e.g., perceived usefulness and intention to continue use),
Artificial Intelligence (e.g., trust in AI features, decision-making assistance),
Customer Behaviour (e.g., usage frequency).
The dataset includes cleaned and anonymized responses and is intended to facilitate further analysis, replication, and model validation in the context of technology adoption. It can be used by researchers interested in smart home adoption, AI perception, behavioral modeling, and digital consumer behavio