Artificial intelligence in online shopping : impact on consumer behaviour
Maharjan, Sanju (2024)
2024
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2024073124045
https://urn.fi/URN:NBN:fi:amk-2024073124045
Tiivistelmä
Artificial Intelligence (AI) has revolutionized retail in the modern era, especially in understanding customer preferences and purchase behaviours.
This study aims to examine the impact of artificial intelligence on consumer trust and confidence in online buying, explore factors contributing to personalized recommendations, assess the challenges faced by online shoppers, and recommend strategies for leveraging artificial intelligence to enhance customer-centric shopping experiences.
This thesis adopts the Technology Acceptance Model (TAM) and Diffusion of Innovation theory to understand how AI influences consumer behaviour and decision-making processes in online shopping.
The research methodology involves interpretivism philosophy, an inductive approach, and primary and secondary qualitative data collection methodologies to gather insight into AI's impacts on customer behaviour. The primary data has been collected from interviews with participants to acknowledge customer behaviour in the online shopping platforms and the impact of AI features on the shopping experiences. The interview verified factors regarding challenges and market situations in which the customer behaviours can be observed and provided recommendations in further acknowledgement.
The research suggests taking privacy concerns must be addressed by e-commerce businesses and personalized recommendations must be incorporated effectively. By considering contextual factors and leveraging AI in a customer-centric manner, businesses can improve customer satisfaction and loyalty in online shopping platforms.
This study aims to examine the impact of artificial intelligence on consumer trust and confidence in online buying, explore factors contributing to personalized recommendations, assess the challenges faced by online shoppers, and recommend strategies for leveraging artificial intelligence to enhance customer-centric shopping experiences.
This thesis adopts the Technology Acceptance Model (TAM) and Diffusion of Innovation theory to understand how AI influences consumer behaviour and decision-making processes in online shopping.
The research methodology involves interpretivism philosophy, an inductive approach, and primary and secondary qualitative data collection methodologies to gather insight into AI's impacts on customer behaviour. The primary data has been collected from interviews with participants to acknowledge customer behaviour in the online shopping platforms and the impact of AI features on the shopping experiences. The interview verified factors regarding challenges and market situations in which the customer behaviours can be observed and provided recommendations in further acknowledgement.
The research suggests taking privacy concerns must be addressed by e-commerce businesses and personalized recommendations must be incorporated effectively. By considering contextual factors and leveraging AI in a customer-centric manner, businesses can improve customer satisfaction and loyalty in online shopping platforms.