Beyond the hype: Organisational adoption of Generative AI through the lens of the TOE framework–A mixed methods perspective

透视图(图形) 相互依存 生成语法 通过镜头测光 钥匙(锁) 知识管理 生成模型 业务 管理科学 过程管理 协同生产 高级管理人员 定性研究 营销 工程类 结构方程建模 定性性质 情感(语言学) 工业4.0
作者
Laurie Hughes,Fern Davies,Keyao Li,Senali Madugoda Gunaratnege,Tegwen Malik,Yogesh K Dwivedi
出处
期刊:International Journal of Information Management [Elsevier BV]
卷期号:86: 102982-102982 被引量:30
标识
DOI:10.1016/j.ijinfomgt.2025.102982
摘要

It is widely accepted that the impact of Generative Artificial Intelligence (GenAI) has been nothing short of transformational, with tangible impacts on industry, education, healthcare and government. But beyond the headlines, how are organisations actually using GenAI, what are the key challenges experienced by decision makers and has the reality on the ground matched the hype? This study adopts a mixed-methods approach, utilising the Technology-Organisation-Environment (TOE) framework to reveal greater insights to how organisations are adopting GenAI, the drivers that affect decision making and the key challenges associated with greater use of the technology. This research adopts a mixed method approach incorporating an explorative qualitative step with industry participants followed by a survey of 304 (three hundred and four) decision makers from a cross section of industry sectors from around the world including: North America, Europe, Africa, Australia and Asia, to gain further insight to the underlying factors that drive GenAI adoption. The research model was validated using Structural Equation Modelling (SEM) and reveals the intricate and inherent complexities related to greater levels of GenAI adoption. The analysis highlights the critical role of change capacity of the organisation in moderating complexity and staff skills. This research provides valuable and timely insights for senior management and policy makers that are attempting to better understand the interdependencies and perspectives on the key challenges facing organisations looking to deliver greater impact on organisational performance through GenAI.
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