Machine learning implementation in small and medium-sized enterprises: insights and recommendations from a quantitative study

被引:0
|
作者
Burggraef, Peter [1 ]
Steinberg, Fabian [1 ]
Sauer, Carl Rene [1 ]
Nettesheim, Philipp [1 ]
机构
[1] Univ Siegen, Chair Int Prod Engn & Management IPEM, Mech Engn, Siegen, Germany
来源
关键词
Data mining readiness; Regression analysis; Machine learning; SME; INNOVATION;
D O I
10.1007/s11740-024-01274-2
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Machine learning (ML) offers high potential in manufacturing industry; moreover, for example the effectiveness of quality prediction and evaluation can be greatly improved using Machine Learning, which can generate significant competitive advantages. However, the potentials of ML are not fully exploited by small and medium-sized enterprises. A qualitative empirical study was conducted with 60 companies from different industry sectors to determine when SMEs are more likely to use ML. Here, it is shown that the willingness to invest in applications is substantial for the implementation of ML. Also, the availability of sufficient qualitative data within the SME is imperative for applying ML. Furthermore, recommendations for action for SMEs are established to close the technology adoption gap in SMEs and to leverage the benefits of ML.
引用
收藏
页码:751 / 764
页数:14
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