Benjamin von Walter , Daniel Wentzel , Stefan Raff
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Should service firms introduce algorithmic advice to their existing customers? The moderating effect of service relationships
An increasing number of service firms are introducing algorithmic advice to their customers. In this research, we examine the introduction of such tools from a relational perspective and show that the type of relationship a customer has with a service firm moderates his or her response to algorithmic advice. Studies 1 and 2 find that customers in communal relationships are more reluctant to use algorithmic advice instead of human advice than customers in exchange relationships. Study 3 shows that offering customers algorithmic advice may harm communal relationships but not exchange relationships. Building on these findings, Studies 4, 5, and 6 examine how firms can mitigate the potentially negative relational consequences of algorithmic advice. While a fallback option that signals that customers can request additional human advice if needed is effective in preventing relational damages in communal relationships, this same intervention backfires in exchange relationships. These findings have important implications by showing that managers need to consider the relational consequences of introducing algorithmic advice to existing customers.
期刊介绍:
The focus of The Journal of Retailing is to advance knowledge and its practical application in the field of retailing. This includes various aspects such as retail management, evolution, and current theories. The journal covers both products and services in retail, supply chains and distribution channels that serve retailers, relationships between retailers and supply chain members, and direct marketing as well as emerging electronic markets for households. Articles published in the journal may take an economic or behavioral approach, but all are based on rigorous analysis and a deep understanding of relevant theories and existing literature. Empirical research follows the scientific method, employing modern sampling procedures and statistical analysis.