Shaping innovation pathways: Metaverse application configurations in high-technology small- and medium-sized enterprises

IF 6.8 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Decision Support Systems Pub Date : 2024-12-01 Epub Date: 2024-09-19 DOI:10.1016/j.dss.2024.114336
Jianwen Zheng , Justin Zuopeng Zhang , Kai Ming Au , Veda C. Storey , Huan Wang , Yifan Yang
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Abstract

The emergence of Industry 4.0, characterized by rapid technological change and fierce competition, challenges technology firms to make strategic innovation decisions. Central to this is the metaverse, a hybrid virtual space combining virtual reality, augmented reality, and the internet. Recognizing that the implications of metaverse applications extend beyond individual organizations, this research examines its adoption configurations. Using the Technology Acceptance Model (TAM) and the Technology-Organization-Environment (TOE) framework, we analyze survey data from 116 high-technology small and medium-sized enterprises in China using fuzzy-set qualitative comparative analysis (fsQCA). Our research reveals that no isolated factor within the TAM-TOE framework solely affects innovation decision-making. Instead, we identify three configurations that enhance decision-making quality and three that increase its speed, leading to improved innovation performance. In this way, this research advances the understanding of technology adoption configurations in the innovation processes of young tech firms.
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塑造创新之路:高科技中小企业的元数据应用配置
以技术快速变革和激烈竞争为特征的工业 4.0 的出现,对技术公司的战略创新决策提出了挑战。其中的核心是元宇宙,这是一个结合了虚拟现实、增强现实和互联网的混合虚拟空间。本研究认识到元宇宙应用的影响超出了单个组织的范围,因此对其采用配置进行了研究。利用技术接受模型(TAM)和技术-组织-环境(TOE)框架,我们使用模糊集定性比较分析法(fsQCA)分析了来自中国 116 家高科技中小企业的调查数据。我们的研究发现,TAM-TOE 框架中没有任何一个孤立的因素会单独影响创新决策。相反,我们确定了三种提高决策质量的配置和三种提高决策速度的配置,从而提高了创新绩效。通过这种方式,本研究推进了对年轻科技企业创新过程中技术采用配置的理解。
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来源期刊
Decision Support Systems
Decision Support Systems 工程技术-计算机:人工智能
CiteScore
14.70
自引率
6.70%
发文量
119
审稿时长
13 months
期刊介绍: The common thread of articles published in Decision Support Systems is their relevance to theoretical and technical issues in the support of enhanced decision making. The areas addressed may include foundations, functionality, interfaces, implementation, impacts, and evaluation of decision support systems (DSSs).
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