影响智能工厂采用工业大数据解决方案的关键障碍

IF 4.5 3区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE
Fei Xing, G. Peng, Jia Wang, Daifeng Li
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引用次数: 6

摘要

工业大数据是实现智能工厂愿景的关键。本研究旨在从社会技术角度识别和探索阻碍组织在智能工厂发展中部署工业大数据解决方案的潜在障碍。该研究采用归纳定性方法。对选定案例公司的首席执行官、智能工厂经理、IT经理、部门负责人和IS顾问进行了27次半结构化访谈。访谈数据采用专题分析法进行分析。根据专题分析,确定了六组障碍,包括技术、数据、技术支持、组织、个人和社会问题,以及它们之间的关系。制定了一个经验框架来强调这些障碍之间的关系。本研究有助于全面了解工业大数据,尤其是为智能工厂发展中的工业大数据实施提供了建设性的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Critical Obstacles Affecting Adoption of Industrial Big Data Solutions in Smart Factories
Industrial big data is the key to realize the vision of smart factories. This research aims to identify and explore potential barriers that prevent organizations from deploying industrial big data solutions in the development of smart factories through a socio-technical perspective. The research follows an inductive qualitative approach. Twenty-seven semi-structured interviews were conducted with the CEO, smart factory manager, IT managers, departmental heads, and IS consultants in the selected case company. The interview data were analyzed using a thematic analysis method. Derived from a thematic analysis, six sets of barriers including technical, data, technical support, organization, individual, and social issues were identified, as well as the relationships between them. An empirical framework was developed to highlight the relationship between these barriers. This study contributes to the knowledge of industrial big data in general and provides constructive insight into industrial big data implementation in smart factory development particularly.
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来源期刊
Journal of Global Information Management
Journal of Global Information Management INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
5.80
自引率
14.90%
发文量
118
期刊介绍: Authors are encouraged to submit manuscripts that are consistent to the following submission themes: (a) Cross-National Studies. These need not be cross-culture per se. These studies lead to understanding of IT as it leaves one nation and is built/bought/used in another. Generally, these studies bring to light transferability issues and they challenge if practices in one nation transfer. (b) Cross-Cultural Studies. These need not be cross-nation. Cultures could be across regions that share a similar culture. They can also be within nations. These studies lead to understanding of IT as it leaves one culture and is built/bought/used in another. Generally, these studies bring to light transferability issues and they challenge if practices in one culture transfer.
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