| Keywords [eng] |
Consumer attitudes, AI-based business, artificial intelligence, AI adoption, consumer perception, consumer behavior, technology acceptance, digital literacy, privacy concerns, transparency, ethical practices, consumer trust, institutional trust, data security, AI ethics, algorithm aversion, psychological ambivalence, perceived usefulness, perceived ease of use, fairness, accountability, GDPR, EU AI Act, responsible AI governance, explainable artificial intelligence, algorithmic bias, personalized marketing, automated customer service, recommendation systems, behavioral intention, consumer acceptance, Lithuania, quantitative research, Likert scale, correlation analysis, ordinal regression |
| Abstract [eng] |
This master’s thesis examines consumer attitudes towards AI-based business, focusing on Lithuania within a broader global context. The relevance of the topic is based on the rapid integration of artificial intelligence into business services such as personalized marketing, automated customer service, recommendation systems, predictive analytics, and digital decision-making. Although AI can improve efficiency, convenience, and personalization, it also raises concerns related to privacy, transparency, fairness, data security, algorithmic bias, and consumer trust. The object of the thesis is consumer perceptions and attitudes toward AI-based business services in Lithuania within a global comparative context. The aim is to investigate how consumers perceive, assess, and ethically evaluate AI-based business services. The study focuses on digital literacy, privacy concerns, transparency, ethical practices, and consumer trust as key factors shaping consumer acceptance or resistance toward AI-based services. The theoretical part of the thesis is based on consumer behavior and technology adoption theories, including the Technology Acceptance Model, the Unified Theory of Acceptance and Use of Technology, and the Theory of Planned Behavior. These theories are extended with AI-specific constructs such as trust, fairness, transparency, privacy, accountability, autonomy, and institutional regulation. The thesis argues that consumer attitudes toward AI are multidimensional because AI-based services are evaluated not only by usefulness or ease of use, but also by ethical, psychological, legal, security, and socio-cultural factors. The empirical part compares Lithuanian and global evidence on AI adoption. The analysis shows that trust is a central factor in consumer acceptance of AI-based business. In Lithuania, consumer trust is strongly influenced by institutional legitimacy, GDPR compliance, EU AI Act principles, fairness, and transparency. The thesis also shows that familiarity with AI does not automatically create trust, as consumers may use AI-based services while still being concerned about privacy, bias, lack of transparency, and loss of control. The research uses a quantitative approach based on a structured survey and a 5-point Likert scale. The main variables analyzed are digital literacy, privacy concerns, transparency, ethical practices, and consumer perception. The collected data are examined using reliability analysis, correlation analysis, and ordinal regression. The results show that the measured constructs are reliable and that significant relationships exist among the main variables. Transparency and ethical practices are especially important because they are strongly connected with consumer trust and positive perception of AI-based business. The findings indicate that consumer acceptance of AI-based business depends not only on technological usefulness, but also on responsible implementation, clear communication, ethical data use, privacy protection, and visible transparency. Overall, the thesis concludes that AI adoption is a technological, psychological, ethical, and institutional process, and consumer trust is essential for the successful use of AI-based business services. |
