I WANT TO BUY LOVE. PLEASE, DON’T BE A ROBOT!

Abstract

Understanding consumer responses to online product recommendations is crucial, particularly for handmade products and when the recommender is either a chatbot or a human. Existing research has mainly focused on factors that enhance chatbot interactions, yet there is scant knowledge about how these digital agents influence consumer responses to products depending on their production mode (handmade vs. machine-made). Addressing this gap, we are interested in uncovering the underlying mechanisms to determine if consumers find these recommenders credible and if they have positive attitudes toward their recommendations. Our research further investigates whether the 'handmade effect' is effectively conveyed when chatbots serve as recommenders. We conducted a 2 (recommender source: human vs. chatbot) × 2 (production mode: machine-made vs. handmade) experiment to test our predictions. Our findings reveal that recommendations from human agents significantly amplify the perception of love in handmade products, thereby positively impacting consumer attitudes and satisfaction. In contrast, chatbot recommendations do not lead to a differentiation between handmade and machine-made products in terms of perceived love, highlighting a shortfall in chatbot-led interactions.