编配
计算机科学
现存分类群
知识管理
桥接(联网)
自动化
过程管理
动态能力
领域(数学)
数据科学
管理科学
工程类
机械工程
艺术
音乐剧
计算机网络
数学
进化生物学
纯数学
视觉艺术
生物
作者
Arun Madanaguli,David Sjödin,Vinit Parida,Patrick Mikalef
标识
DOI:10.1016/j.techfore.2023.123189
摘要
This study explores the interlink between AI capabilities and circular business models (CBMs) through a literature review. Extant literature reveals that AI can act as efficiency catalyst, empowering firms to implement CBM. However, the journey to harness AI for CBM is fraught with challenges as firms grapple with the lack of sophisticated processes and routines to tap into AI's potential. The fragmented literature leaves a void in understanding the barriers and development pathways for AI capabilities in CBM contexts. Bridging this gap, adopting a capabilities perspective, this review intricately brings together four pivotal capabilities: integrated intelligence capability, process automation and augmentation capability, AI infrastructure and platform capability, and ecosystem orchestration capability as drivers of AI-enabled CBM. These capabilities are vital to navigating the multi-level barriers to utilizing AI for CBM. The key contribution of the study is the synthesis of an AI-enabled CBM framework, which not only summarizes the results but also sets the stage for future explorations in this dynamic field.
科研通智能强力驱动
Strongly Powered by AbleSci AI