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Innovation Performance Prediction of University Student Teams Based on Bayesian Networks

Author

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  • Xueliang Zhang

    (Department of Industrial Engineering, Northwestern Polytechnical University, Xi’an 710072, China)

  • Jiawei Liu

    (School of Public Policy and Administration, Northwestern Polytechnical University, Xi’an 710072, China)

  • Chi Zhang

    (Department of Industrial Engineering, Northwestern Polytechnical University, Xi’an 710072, China)

  • Dongyan Shao

    (School of Life Sciences, Northwestern Polytechnical University, Xi’an 710072, China)

  • Zhiqiang Cai

    (Department of Industrial Engineering, Northwestern Polytechnical University, Xi’an 710072, China)

Abstract

Many studies have been conducted on the impact of dualistic learning, knowledge sharing, member heterogeneity, and their influencing factors on team performance in enterprises. However, research on the substantial differences between university student teams and enterprise teams is scarce. To address this void, this empirical study explores how the mechanism of dualistic learning affects university student teams’ learning performance facing rapid changes in higher education. Using the questionnaire, two modules of dualistic learning were identified through reliability and validity tests, and the research data set was formed. After preprocessing the data set, two team innovation performance prediction models were established based on the Bayesian network (BN). According to the characteristics of BN, the probability reasoning of the model was calculated and the posterior probability table was obtained under different dualistic learning levels. The results show that dualistic learning has significant impacts on innovation performance, and the improvement of dualistic learning can stimulate team innovation performance. This research can provide important theoretical guidance for teams to improve their ability, gain competitive advantages, and stimulate the creative enthusiasm of college students. Hopefully, this research will enrich the existing theoretical connotation to a certain extent and promote the development of relevant empirical research.

Suggested Citation

  • Xueliang Zhang & Jiawei Liu & Chi Zhang & Dongyan Shao & Zhiqiang Cai, 2023. "Innovation Performance Prediction of University Student Teams Based on Bayesian Networks," Sustainability, MDPI, vol. 15(3), pages 1-17, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:3:p:2335-:d:1048467
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    References listed on IDEAS

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    1. James G. March, 1991. "Exploration and Exploitation in Organizational Learning," Organization Science, INFORMS, vol. 2(1), pages 71-87, February.
    2. Vinoth Kumar Ponnusamy & Padmanathan Kasinathan & Rajvikram Madurai Elavarasan & Vinoth Ramanathan & Ranjith Kumar Anandan & Umashankar Subramaniam & Aritra Ghosh & Eklas Hossain, 2021. "A Comprehensive Review on Sustainable Aspects of Big Data Analytics for the Smart Grid," Sustainability, MDPI, vol. 13(23), pages 1-35, December.
    3. Zhongyuan Gu & Miaocong Cao & Chunguang Wang & Na Yu & Hongyu Qing, 2022. "Research on Mining Maximum Subsidence Prediction Based on Genetic Algorithm Combined with XGBoost Model," Sustainability, MDPI, vol. 14(16), pages 1-12, August.
    4. Jian Ma & Hua Su & Wan-lin Zhao & Bin Liu, 2018. "Predicting the Remaining Useful Life of an Aircraft Engine Using a Stacked Sparse Autoencoder with Multilayer Self-Learning," Complexity, Hindawi, vol. 2018, pages 1-13, July.
    5. Morten T. Hansen, 2002. "Knowledge Networks: Explaining Effective Knowledge Sharing in Multiunit Companies," Organization Science, INFORMS, vol. 13(3), pages 232-248, June.
    6. Chenyang Ma & Wei Wang & Zhiqiang Cai & Jiangbin Zhao, 2022. "Maintenance optimization of reconfigurable systems based on multi-objective Birnbaum importance," Journal of Risk and Reliability, , vol. 236(2), pages 277-289, April.
    7. Zhiang (John) Lin & Haibin Yang & Irem Demirkan, 2007. "The Performance Consequences of Ambidexterity in Strategic Alliance Formations: Empirical Investigation and Computational Theorizing," Management Science, INFORMS, vol. 53(10), pages 1645-1658, October.
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    Cited by:

    1. Keqin Wang & Ting Wang & Tianyi Wang & Zhiqiang Cai, 2024. "Research on Evaluation Methods for Sustainable Enrollment Plan Configurations in Chinese Universities Based on Bayesian Networks," Sustainability, MDPI, vol. 16(7), pages 1-19, April.
    2. Zongjun Zhang & Qian Deng & Wei He & Cuiping Yang, 2024. "A New Method Based on Belief Rule Base with Balanced Accuracy and Interpretability for Student Achievement Prediction," Mathematics, MDPI, vol. 12(20), pages 1-21, October.

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