Research on enterprise business model and technology innovation based on artificial intelligence

Abstract Small- and medium-sized enterprises (SEMs) are the important part of economic society whose innovation activities are of great significance for building innovative country. In order to investigate how technological innovation (TI) and business model design (BMD) affect the business performa...

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Main Authors: Sunping Qu, Hongwei Shi, Huanhuan Zhao, Lin Yu, Yunbo Yu
Format: Article
Language:English
Published: SpringerOpen 2021-07-01
Series:EURASIP Journal on Wireless Communications and Networking
Subjects:
Online Access:https://doi.org/10.1186/s13638-021-02025-y
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author Sunping Qu
Hongwei Shi
Huanhuan Zhao
Lin Yu
Yunbo Yu
author_facet Sunping Qu
Hongwei Shi
Huanhuan Zhao
Lin Yu
Yunbo Yu
author_sort Sunping Qu
collection DOAJ
description Abstract Small- and medium-sized enterprises (SEMs) are the important part of economic society whose innovation activities are of great significance for building innovative country. In order to investigate how technological innovation (TI) and business model design (BMD) affect the business performance of SMEs, samples of 268 SMEs in the artificial intelligence industry and hierarchical regression models are used in the analysis. The results indicate that TI, BMD, and the matching of them have different effects on the innovation of SMEs of different sizes. These findings are helpful for enriching the theory of the fit between TI and BMD and providing theoretical guidance for the innovation activities in SEMs.
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spelling doaj.art-ec93df1398d54da49aba5959a1525d932022-12-21T22:05:54ZengSpringerOpenEURASIP Journal on Wireless Communications and Networking1687-14992021-07-012021111910.1186/s13638-021-02025-yResearch on enterprise business model and technology innovation based on artificial intelligenceSunping Qu0Hongwei Shi1Huanhuan Zhao2Lin Yu3Yunbo Yu4School of Management, JiangSu UniversitySchool of Management, JiangSu UniversityCollege of Management, Wuxi Institute of TechnologyCollege of Management, Wuxi Institute of TechnologyCollege of Management, Wuxi Institute of TechnologyAbstract Small- and medium-sized enterprises (SEMs) are the important part of economic society whose innovation activities are of great significance for building innovative country. In order to investigate how technological innovation (TI) and business model design (BMD) affect the business performance of SMEs, samples of 268 SMEs in the artificial intelligence industry and hierarchical regression models are used in the analysis. The results indicate that TI, BMD, and the matching of them have different effects on the innovation of SMEs of different sizes. These findings are helpful for enriching the theory of the fit between TI and BMD and providing theoretical guidance for the innovation activities in SEMs.https://doi.org/10.1186/s13638-021-02025-yTechnological innovationBusiness model designBusiness performanceEnterprise sizeArtificial intelligence
spellingShingle Sunping Qu
Hongwei Shi
Huanhuan Zhao
Lin Yu
Yunbo Yu
Research on enterprise business model and technology innovation based on artificial intelligence
EURASIP Journal on Wireless Communications and Networking
Technological innovation
Business model design
Business performance
Enterprise size
Artificial intelligence
title Research on enterprise business model and technology innovation based on artificial intelligence
title_full Research on enterprise business model and technology innovation based on artificial intelligence
title_fullStr Research on enterprise business model and technology innovation based on artificial intelligence
title_full_unstemmed Research on enterprise business model and technology innovation based on artificial intelligence
title_short Research on enterprise business model and technology innovation based on artificial intelligence
title_sort research on enterprise business model and technology innovation based on artificial intelligence
topic Technological innovation
Business model design
Business performance
Enterprise size
Artificial intelligence
url https://doi.org/10.1186/s13638-021-02025-y
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