Evaluation of enterprise technology innovation capability in prefabricated construction in China

Purpose This study aims to evaluate enterprise technology innovation capability in prefabricated construction (PC) from an input-output perspective, using six integrated enterprises in China as cases. Design/methodology/approach An evaluation system for enterprise technology innovation capability in...

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Bibliographic Details
Published inConstruction innovation Vol. 22; no. 4; pp. 1059 - 1084
Main Authors Dou, Yudan, Xue, Xiaolong, Wang, Yuna, Xue, Weirui, Huangfu, Wenbo
Format Journal Article
LanguageEnglish
Published London Emerald Publishing Limited 28.11.2022
Emerald Group Publishing Limited
Subjects
Carbon
Cognitive maps
Construction industry
Energy consumption
Entropy (Information theory)
Innovations
Manufacturing
Performance indices
Prefabricated buildings
Prefabrication
R&D
Research & development
Sustainability
Technology
China
Evaluation
Prefabricated construction
Enterprises
Combined weights
China
Technology innovation capability
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Summary:Purpose This study aims to evaluate enterprise technology innovation capability in prefabricated construction (PC) from an input-output perspective, using six integrated enterprises in China as cases. Design/methodology/approach An evaluation system for enterprise technology innovation capability in PC was constructed, including total input, technology output (TO) and project output. All the evaluation indexes were quantified, and the subject and object indexes weights were determined using the fuzzy cognitive map and information entropy, respectively. The final scores and ranks were evaluated through gray relational analysis (GRA) based on the combined weights. Findings It was found that enterprise technology innovation capability in PC was low in China, with its unbalanced development in different dimensions and the poorest performance in TO, currently. Originality/value This research has developed an evaluation system for technology innovation capability in PC at the enterprise level and scientifically quantified all the indexes, which is a breakthrough over existing studies. The GRA model based on the combined weights proposed in this study can be applied to other comparable fields and regions, with its easy operation.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1471-4175
1471-4175
1477-0857
DOI:10.1108/CI-12-2020-0196