相互依存
业务
声誉
托换
知识管理
战略规划
集合(抽象数据类型)
现存分类群
战略管理
营销
计算机科学
社会学
工程类
土木工程
生物
进化生物学
程序设计语言
社会科学
作者
Yongqiang Sun,Chee‐Wee Tan,Kai H. Lim,Ting‐Peng Liang,Yi‐Hsuan Yeh
摘要
Abstract Despite the broad application of the technology–organisation–environment (TOE) framework to explain firms' adoption of technology, prior research tends to over‐emphasise the independent effects of TOE elements while neglecting decision makers' strategic orientations when making organisational technology adoption decisions. This over‐simplistic interpretation of the TOE framework has culminated in inconsistent findings within extant literature. Considering the interdependencies among the three TOE elements in shaping organisational technology adoption and also decision‐makers' inclination to weigh the three TOE elements differently based on their strategic orientations, this study views organisational technology adoption from a systems standpoint based on a configurational approach. Particularly, we differentiate between two types of strategic orientations, namely functional orientation, which accentuates the technology‐induced efficiency gains and symbolic orientation, which stresses the image or reputation afforded through technology adoption. We advance a configurational model for organisational technology adoption that: (1) conceptualises organisational technology adoption as an outcome arising from distinct configurations of TOE elements, and; (2) extends the TOE framework by incorporating strategic orientation as an inevitable aspect of decision‐making for organisational technology adoption. To validate our proposed model, we conducted a field survey of 183 firms to collect data on their considerations underpinning organisational technology adoption before employing fuzzy‐set Qualitative Comparative Analysis to derive configurations of TOE elements responsible for driving such adoption. Analytical results reveal that the TOE configurations vary across three types of organisations (namely performance enhancer, image builder and strategic transformer). The theoretical and practical implications of our study are also discussed.
科研通智能强力驱动
Strongly Powered by AbleSci AI