Assessing the Impact of Recommendation Novelty on Older Consumers: Older Does Not Always Mean the Avoidance of Innovative Products

Author:

Zhao Li1,Fu Bing1ORCID

Affiliation:

1. College of Business Administration, Capital University of Economics and Business, Beijing 100070, China

Abstract

Personalized recommendations that use digital technologies to predict user interests and preferences and give guiding conclusions have become a widely used digital marketing tool on e-commerce platforms. Given that existing consumer behavior research has not reached a consensus on the relationship between age and the adoption of innovative products, whether recommendation novelty can stimulate older consumers’ acceptance of innovative products remains uncertain. Grounded in the aging and social influence literature, this experimental study investigated the moderating role of individual cognitive age on the impact of recommendation novelty on consumer perceptions regarding stereotype threat and receptiveness to innovativeness. An experiment involving 239 online shoppers was conducted to investigate the experiences of cognitively younger and older adults while using low or high levels of recommendation novelty designed for this study. Results reveal the tension for older adults when using highly recommended novelty, as they perceive these to be more of a stereotype threat, but they also have a higher level of receptiveness to innovativeness. This finding is contrary to the common belief that “the older the consumer, the less receptive to innovativeness”, providing novel insight into the information systems literature. Theoretically, this research shows how increasing the level of recommended novelty affects stereotype threat and receptiveness to innovativeness (of consumers of different cognitive ages). For practitioners, the results provide important guidelines on the kind of personalized recommendations that are appropriate for consumers with different cognitive ages.

Funder

National Social Science Fund of China

Publisher

MDPI AG

Reference101 articles.

1. Assessing the design choices for online recommendation agents for older adults: Older does not always mean simpler information technology;Ghasemaghaei;MIS Q.,2019

2. Enhancing brick-and-mortar store shopping experience with an augmented reality shopping assistant application using personalized recommendations and explainable artificial intelligence;Zimmermann;J. Res. Interact. Mark.,2023

3. Towards understandable personalized recommendations: Hybrid explanations;Svrcek;Comput. Sci. Inf. Syst.,2019

4. I want it my way! The effect of perceptions of personalization through augmented reality and online shopping on customer intentions to co-create value;Alimamy;Comput. Hum. Behav.,2022

5. Credibility score based multi-criteria recommender system;Gupta;Knowl.-Based Syst.,2020

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