生成语法
知识管理
生成模型
结构方程建模
独创性
信息系统
客户关系管理
心理学
业务
计算机科学
营销
社会心理学
人工智能
工程类
电气工程
机器学习
创造力
作者
Aman Kumar,Amit Shankar
出处
期刊:Journal of Business & Industrial Marketing
[Emerald Publishing Limited]
日期:2025-08-11
卷期号:40 (8): 1593-1614
被引量:4
标识
DOI:10.1108/jbim-06-2024-0433
摘要
Purpose This study aims to explore the factors influencing organizational adoption of Generative AI-enabled customer relationship management (CRM) systems. Design/methodology/approach A multi-study research design has been used to fulfil the study’s objectives. First, a qualitative study explores the crucial factors that may influence adoption towards Generative AI-enabled CRM systems. Further, the research framework based on the findings of qualitative studies is validated using quantitative research (structural equation modelling approach). Findings The findings of this study reveal that amenability barriers negatively influence Generative AI-enabled CRM systems adoption. Further, the results reveal that the information values and convenience values are significantly associated with Generative AI-enabled CRM systems adoption. Additionally, the results also reveal that Generative AI-enabled CRM systems adoption is significantly associated with organizational agility. Also, the results reveal that perceived trust mediates the association between social values, information values and Generative AI-enabled CRM systems adoption. Moreover, the findings also highlighted that technostress significantly moderates the association between perceived distrust, perceived trust and Generative AI-enabled CRM system adoption. Originality/value This study provides a deeper understanding of organizational behavioural intentions towards Generative AI-enabled CRM systems using the underpinnings of the theory of consumption values and innovation resistance theory. The study helps organizational top management understand the factors associated with enhancing the adoption and usage of Generative AI-enabled CRM systems.
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