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Interdisciplinary Teaching Reform of Financial Engineering Majors Based on the Analytic Hierarchy Process in the Post-Pandemic Era

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  • Lihui Xiong

    (School of Business, Wenzhou University, Wenzhou 325035, China)

  • Ximiao Dong

    (School of Management, Lanzhou University, Lanzhou 730000, China)

  • Jiaqi Fang

    (School of Business, Wenzhou University, Wenzhou 325035, China)

Abstract

In the post-epidemic era, the labor market has become increasingly complex, making it even more crucial to incorporate sustainability into employment demand. As we enter the post-pandemic era, a globalization trend has become more apparent. It is crucial to modernize employability through educational reform in order to assist employees in enhancing their professional skills. This study began by analyzing the importance of financial engineering practice instruction and graduate employability in the post-epidemic era. Second, the study proposed the content and a plan for inter-disciplinary teaching reform to address talent cultivation needs based on labor market requirements. Third, a face-to-face survey and interview were conducted with students affected by changes in teaching, and the results were analyzed and summarized. On this basis, the impact of education reform was evaluated using both the expert scoring method and the analytic hierarchy approach. The results indicated that the suggested financial engineering teaching reform program improved the school’s discipline strength, enrollment rate, employment rate, and competition awards, especially discipline strength. This research can be used to inform the teaching of financial engineering majors in various countries, assist job candidates in enhancing their professional skills, and build a formidable talent pool for the labor market.

Suggested Citation

  • Lihui Xiong & Ximiao Dong & Jiaqi Fang, 2023. "Interdisciplinary Teaching Reform of Financial Engineering Majors Based on the Analytic Hierarchy Process in the Post-Pandemic Era," Sustainability, MDPI, vol. 15(11), pages 1-17, May.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:11:p:8652-:d:1156677
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    References listed on IDEAS

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    1. Bo Gao, 2022. "The Use of Machine Learning Combined with Data Mining Technology in Financial Risk Prevention," Computational Economics, Springer;Society for Computational Economics, vol. 59(4), pages 1385-1405, April.
    2. Erol Eğrioğlu & Robert Fildes, 2022. "A New Bootstrapped Hybrid Artificial Neural Network Approach for Time Series Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 59(4), pages 1355-1383, April.
    3. Emmanuel Thanassoulis & Prasanta Kumar Dey & Konstantinos Petridis & Ioannis Goniadis & Andreas C. Georgiou, 2017. "Evaluating higher education teaching performance using combined analytic hierarchy process and data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(4), pages 431-445, April.
    4. Xiaoqun Wang, 2016. "Handling Discontinuities in Financial Engineering: Good Path Simulation and Smoothing," Operations Research, INFORMS, vol. 64(2), pages 297-314, April.
    5. Singleton, Kenneth J., 2001. "Estimation of affine asset pricing models using the empirical characteristic function," Journal of Econometrics, Elsevier, vol. 102(1), pages 111-141, May.
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