Factors Affecting the Adoption of Blockchain Technology in the Complex Industrial Systems: Data Modeling
Nowadays, Blockchain Technology (BCT) is contributing toward addressing the challenges of complex industrial systems (CISs). The BCT reduces the complexity of cash data storage as well as retrieval system of finance, marketing, supply chain, inventory, and other departments. The objective of the pre...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/8329487 |
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| author | Yu Chengyue M. Prabhu Mahendar Goli Anoop Kumar Sahu |
| author_facet | Yu Chengyue M. Prabhu Mahendar Goli Anoop Kumar Sahu |
| author_sort | Yu Chengyue |
| collection | DOAJ |
| description | Nowadays, Blockchain Technology (BCT) is contributing toward addressing the challenges of complex industrial systems (CISs). The BCT reduces the complexity of cash data storage as well as retrieval system of finance, marketing, supply chain, inventory, and other departments. The objective of the present study is to investigate the factors, which affect the intention of professionals to adapt the BCT in the CISs by using an extension of the technology acceptance model. To fulfill the research objective, a theoretical research model is constituted by multiple hypotheses (H1–H6), i.e., perceived usefulness, perceived ease of use, perceived innovativeness, knowledge, risk, and trust after conducting the relevant literature survey in the context of BCT. Next, each hypothesis is tested by exploring the survey data of a sample of 287 professionals of different BCT user’s companies such as retailing, e-commerce, manufacturing, and construction. Survey data is analyzed by executing the structural equation modeling with AMOS software. The factors and latent constructs loadings, reliability, convergent, discriminant, model fit-measurement, structural model, and the path analysis are conducted. The results reveal that the H1, H2, and H4–H6 dropped the positive impact and effect on professionals’ intention to use the BCT in CISs. But, H3 has no effect for enhancing the intention of professionals to use BCT. |
| format | Article |
| id | doaj-art-ef2d8467e6d94f178ed49460c7854bce |
| institution | Kabale University |
| issn | 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-ef2d8467e6d94f178ed49460c7854bce2025-02-03T01:20:38ZengWileyComplexity1099-05262021-01-01202110.1155/2021/8329487Factors Affecting the Adoption of Blockchain Technology in the Complex Industrial Systems: Data ModelingYu Chengyue0M. Prabhu1Mahendar Goli2Anoop Kumar Sahu3School of Economics and ManagementDepartment of Business AdministrationSchool of ManagementDepartment of Mechanical EngineeringNowadays, Blockchain Technology (BCT) is contributing toward addressing the challenges of complex industrial systems (CISs). The BCT reduces the complexity of cash data storage as well as retrieval system of finance, marketing, supply chain, inventory, and other departments. The objective of the present study is to investigate the factors, which affect the intention of professionals to adapt the BCT in the CISs by using an extension of the technology acceptance model. To fulfill the research objective, a theoretical research model is constituted by multiple hypotheses (H1–H6), i.e., perceived usefulness, perceived ease of use, perceived innovativeness, knowledge, risk, and trust after conducting the relevant literature survey in the context of BCT. Next, each hypothesis is tested by exploring the survey data of a sample of 287 professionals of different BCT user’s companies such as retailing, e-commerce, manufacturing, and construction. Survey data is analyzed by executing the structural equation modeling with AMOS software. The factors and latent constructs loadings, reliability, convergent, discriminant, model fit-measurement, structural model, and the path analysis are conducted. The results reveal that the H1, H2, and H4–H6 dropped the positive impact and effect on professionals’ intention to use the BCT in CISs. But, H3 has no effect for enhancing the intention of professionals to use BCT.http://dx.doi.org/10.1155/2021/8329487 |
| spellingShingle | Yu Chengyue M. Prabhu Mahendar Goli Anoop Kumar Sahu Factors Affecting the Adoption of Blockchain Technology in the Complex Industrial Systems: Data Modeling Complexity |
| title | Factors Affecting the Adoption of Blockchain Technology in the Complex Industrial Systems: Data Modeling |
| title_full | Factors Affecting the Adoption of Blockchain Technology in the Complex Industrial Systems: Data Modeling |
| title_fullStr | Factors Affecting the Adoption of Blockchain Technology in the Complex Industrial Systems: Data Modeling |
| title_full_unstemmed | Factors Affecting the Adoption of Blockchain Technology in the Complex Industrial Systems: Data Modeling |
| title_short | Factors Affecting the Adoption of Blockchain Technology in the Complex Industrial Systems: Data Modeling |
| title_sort | factors affecting the adoption of blockchain technology in the complex industrial systems data modeling |
| url | http://dx.doi.org/10.1155/2021/8329487 |
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