Search Conferences

Type in any word, words or author name. This searchs through the abstract title, keywords and abstract text and authors. You may search all conferences or just select one conference.


 All Conferences
 EMAC 2019 Annual Conference
 EMAC 2020 Annual Conference
 EMAC 2020 Regional Conference
 EMAC 2021 Annual Conference
 EMAC 2021 Regional Conference
 EMAC 2022 Annual
 EMAC 2022 Regional Conference
 EMAC 2023 Annual
 EMAC 2023 Regional Conference
 EMAC 2024 Annual
 EMAC 2024 Regional Conference

EMAC 2024 Annual


The impact of AI on the role of communication in B2B relationships
(A2024-119352)

Published: May 28, 2024

AUTHORS

Suh-Young Park, University of Auckland; Jongwon Park, Korea University Business School

ABSTRACT

Effective communication is crucial for service providers to establish long-term relationships with B2B customers. The present research explores the impact of AI on the role of communication in B2B relationships. Specifically, we examine the relative impact of two types of communication (relational communication vs. project-specific communication) on satisfaction and the moderating influence of service type (AI-based vs. human-based). To do so, we conducted an online experiment in which the communication type and the service type were manipulated. Then, data were analyzed by both ANOVA analysis and fsQCA (fuzzy-set Qualitative Comparative Analysis) to establish convergent validity of findings. Results from both analyses indicate that the impact of relational communication on satisfaction is particularly important in AI-based services. In contrast, the effect of project-specific communication is more critical in human-based services. These findings extend the literature in several ways. First, we demonstrate that the relative impact of two types of communication – relational (which focuses on building a relationship) and project-specific (which is task-oriented) – on satisfaction depends on the type of service provided (AI-based or human-based). Second, we use two qualitatively distinct methods: a statistical method (ANOVA) and a set-theoretic method (fsQCA; Fuzzy-set Qualitative Comparative Analysis) to analyze our data and demonstrate that using multiple methods can provide the convergent validity of our findings. Finally, our results have important managerial implications for service providers seeking to establish long-term relationships with their B2B customers.