{"title":"A study on the impact of entrepreneurial bricolage on enterprise performance management using the BPNN-DEMATEL method and social network analysis","authors":"Xi Kang , Saiyong Li , Kanchaya Chaivirutnukul","doi":"10.1016/j.techsoc.2025.102883","DOIUrl":null,"url":null,"abstract":"<div><div>With the advancement of artificial intelligence (AI), intelligent methods have become increasingly important for optimizing enterprise development strategies. This study applies the Back Propagation Neural Network-Decision Making Trial and Evaluation Laboratory (BPNN-DEMATEL) method and social network analysis to improve strategic decision-making for emerging enterprises. First, the BPNN-DEMATEL method is developed based on Back Propagation Neural Network (BPNN) and the Decision-Making Trial and Evaluation Laboratory (DEMATEL). Then, it is refined using insights from social network analysis. Finally, the model is evaluated to assess its effectiveness in analyzing performance management strategies. Results indicate that the BPNN-DEMATEL model improves calculation accuracy by approximately 23 %–47 % and reduces reaction time by 20 %–50 % compared to existing models. After optimization, integrating social network analysis further enhances accuracy, increasing it by 38 %–70 %. Additionally, the model effectively examines the impact of entrepreneurial bricolage on performance management, providing insights that support new venture development. These findings contribute to the optimization and practical application of AI in enterprise strategy, offering both technical and theoretical foundations for business growth in the digital era.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"82 ","pages":"Article 102883"},"PeriodicalIF":10.1000,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Technology in Society","FirstCategoryId":"90","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0160791X25000739","RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SOCIAL ISSUES","Score":null,"Total":0}
引用次数: 0
Abstract
With the advancement of artificial intelligence (AI), intelligent methods have become increasingly important for optimizing enterprise development strategies. This study applies the Back Propagation Neural Network-Decision Making Trial and Evaluation Laboratory (BPNN-DEMATEL) method and social network analysis to improve strategic decision-making for emerging enterprises. First, the BPNN-DEMATEL method is developed based on Back Propagation Neural Network (BPNN) and the Decision-Making Trial and Evaluation Laboratory (DEMATEL). Then, it is refined using insights from social network analysis. Finally, the model is evaluated to assess its effectiveness in analyzing performance management strategies. Results indicate that the BPNN-DEMATEL model improves calculation accuracy by approximately 23 %–47 % and reduces reaction time by 20 %–50 % compared to existing models. After optimization, integrating social network analysis further enhances accuracy, increasing it by 38 %–70 %. Additionally, the model effectively examines the impact of entrepreneurial bricolage on performance management, providing insights that support new venture development. These findings contribute to the optimization and practical application of AI in enterprise strategy, offering both technical and theoretical foundations for business growth in the digital era.
期刊介绍:
Technology in Society is a global journal dedicated to fostering discourse at the crossroads of technological change and the social, economic, business, and philosophical transformation of our world. The journal aims to provide scholarly contributions that empower decision-makers to thoughtfully and intentionally navigate the decisions shaping this dynamic landscape. A common thread across these fields is the role of technology in society, influencing economic, political, and cultural dynamics. Scholarly work in Technology in Society delves into the social forces shaping technological decisions and the societal choices regarding technology use. This encompasses scholarly and theoretical approaches (history and philosophy of science and technology, technology forecasting, economic growth, and policy, ethics), applied approaches (business innovation, technology management, legal and engineering), and developmental perspectives (technology transfer, technology assessment, and economic development). Detailed information about the journal's aims and scope on specific topics can be found in Technology in Society Briefings, accessible via our Special Issues and Article Collections.