In the world of e-commerce, companies are always looking for ways to make smart decisions about their investments and marketing strategies. One important area is understanding how artificial intelligence-based digital technology shopping assistants can affect customers’ satisfaction and their intention to make purchases. That’s what our study is all about.
I. Research Methods
- Tools Used: We used two software programs, SPSS 26.0 and Amos 26.0, to do different types of analyses. These helped us look at things like how often certain behaviors happened (frequency), what factors were important, and how different groups of people might respond differently.
- Analyses Conducted: We carried out analyses like SEM and multiple group analysis. This way, we could dig deeper into the relationships between different elements. This will see how they all worked together to influence consumers.
II. Results
1. Categories of AI Shopping Assistant
- Four Types: We found that the elements that motivate consumer innovativeness when it comes to AI shopping assistants can be put into four groups. There are the functional ones, like how well the assistant helps with tasks like searching for products. Then there’s the hedonic aspect, which is about making shopping more enjoyable. The rational part has to do with helping consumers make sensible choices, and the reliable element is about how trustworthy the assistant seems.
- Examples: For example, a functional element could be a good search function that quickly finds the product you want. A hedonic element might be if the assistant has a friendly way of chatting with you while you shop.
2. Impact on Satisfaction and Purchase Intention
- Satisfaction Impact: We saw that two of these elements, hedonic and rational, had a big effect on how satisfied consumers were with the AI shopping assistant. So, if the shopping experience was fun and also helped them make smart decisions, they were more likely to be happy with it.
- Purchase Intention Impact: When it came to the intention to buy something, the rational and functional elements mattered a lot. That means if the assistant helped them compare prices and find things easily, they were more likely to want to make a purchase. But interestingly, we found that overall satisfaction with the AI shopping assistant didn’t actually lead to a higher purchase intention.
3. Group Differences
- Hedonic Aspect: In the case of the hedonic element, we noticed that the group of people who preferred AI shopping assistants had a stronger feeling of satisfaction compared to those who liked human help better. So, when shopping was made more enjoyable by the AI, these consumers really liked it.
- Rational Aspect: However, when it came to the rational element, there wasn’t much difference between different groups in terms of purchase intention. Whether someone liked AI or human help, if the assistant helped them make good decisions, it didn’t really change how likely they were to buy something.
III. What It Means for Companies
1. Importance of Certain Features
- Comparative Information: When companies are thinking about introducing AI shopping assistants. It’s really important to include features that let consumers compare basic information, like product prices. This helps with the rational aspect and makes it more likely that consumers will use the assistant.
- Functionality: Also, having good search functions and making sure the assistant works well with the payment system is key. These functional elements make shopping easier and more convenient, which can encourage consumers to make purchases.
Our study shows that consumers like AI shopping assistants in e-commerce because they can shop in a sensible way and enjoy the functional benefits. By understanding these factors and how they impact satisfaction and purchase intention. Companies can make better decisions about what to include in their AI shopping assistants to attract more customers and boost sales.
