报告摘要：
Generative artificial intelligence has accelerated the development of organizational innovative productivity, which introduces challenges in the adoption of new technologies by organizations. Publicly listed enterprises exhibit hesitation in adopting generative AI due to a lack of organizational readiness, which reflects their capacity to effectively embrace new technologies. This paper conducts discourse analysis on the Q&A data from earnings conference calls of publicly 461 listed companies, leveraging a large language model’s capability in decision-making and theoretical framework classification concerning generative AI content. Through this approach, we develop a theoretical framework for organizational readiness for the adoption of generative AI. This framework includes 26 measurement indicators, categorized under eight constructs: Resource readiness, IT readiness, Cognitive readiness, Partnership readiness, Innovation valance, Strategic readiness, Cultural readiness, and IT governance readiness. Our study advances theoretical research on GenAI adoption by developing a framework of organizational readiness, enriched by the integration of large language models and discourse analysis, offering a scalable and comprehensive approach to understanding and constructing theory.
嘉宾简介：
徐东溟，昆士兰大学商学院商业信息系统副教授，香港城市大学信息系统博士，IM副主编、AJIS编委，PACIS执行委员会成员，多届PACIS、ECIS、AMCIS、HICSS、 ECIS、ACIS等联合主席，在国际高水平期刊会议发表文章70余篇。她的研究专注于信息技术的使用与创新的结合，致力于深入理解信息系统的运作方式及其对社会的深远影响。近年来，她将研究重点放在了IT创业领域，特别是探索高科技初创企业的成长路径以及IT创新如何与企业业务绩效相互促进。同时，其研究兴趣还包括对社交媒体在商业操作中的应用，如在灾害管理、电子金融和电子健康等关键领域的实践等。
