Consumer acceptance of product innovations

This dissertation contributes to the field of consumer acceptance of product innovations (including new products and services) by examining three important determinants, namely two product characteristics (i.e., artificial intelligence (AI) integration into service and product typicality) and one branding strategy for new products (i.e., brand extensions).
Chapter 2 considers emerging new services in which AI is employed to serve consumers. Results show that consumers refuse AI for tasks that require high warmth due to the low fit between AI and the task at hand. Moreover, an AI-human collaboration where AI supports a human employee increases consumer acceptance of AI for tasks that require high warmth. Unexpectedly, this is not the case for AI-human collaboration of AI supervised by a human employee.
Chapter 3 investigates how the typicality of a new product within its product category influences product performance. Results reveal that product typicality positively influences new product success via reliability, but negatively affects it via excitement. Moreover, we find that individualism moderates the typicality-new product success relationship by mitigating (strengthening) the positive (negative) effect of typicality on reliability (excitement). Uncertainty avoidance, though, moderates that association in the opposite way.
Chapter 4 investigates drivers of an important branding strategy for new products, namely brand extensions. Results reveal the most influential drivers of brand extension success are parent brand strength and brand extension fit. A moderator analysis yields new boundary conditions for these two drivers. For example, parent brand industry type is an important moderator.