摘要
在当前由大数据、云计算及人工智能技术创新引领的科技革命背景下,企业对于人才的评价标准与需求结构正经历着前所未有的变革与重塑。研究聚焦于应用型本科高校财务管理专业,通过分析与优化大数据技术趋势下相关专业课程设置,以培养出更能适应市场需求的高素质财务顾问。运用清晰集定性比较分析方法,深入剖析影响其职业晋升的关键能力构成,为应用型高校的财务管理专业人才培养体系精准开设大数据相关课程提供实证依据,进而为应用型高等教育财经类专业大数据改革提供建议。
In the context of the current technological revolution driven by innovations in big data,cloud computing,and artificial intelligence,the standards for evaluating corporate talent and the structure of demand are undergoing unprecedented changes and reshaping.This study focuses on the financial management major in application-oriented universities,aiming to analyze and optimize the curriculum related to big data technology trends to cultivate high-quality financial advisors who can better respond to market demands.The article uses crisp set Qualitative Comparative Analysis(csQCA),it deeply analyzes the key capability composition affecting their career advancement.The goal is to provide empirical evidence for precisely establishing big data-related courses in the financial management major at application-oriented universities,thereby offering suggestions for the big data reform of finance-related majors in applied higher education.
作者
鞠铨
王玉冬
姜庆春
Ju Quan;Wang Yudong;Jiang Qingchun(Heilongjiang University of Finance and Economic,Harbin Heilongjiang 150500;Harbin University of Science and Technology,Harbin Heilongjiang 150080)
出处
《对外经贸》
2025年第12期154-160,共7页
FOREIGN ECONOMIC RELATIONS & TRADE
基金
基于ChatGPT的财务管理大数据课程优化研究(项目编号:XJYB2024046)。
关键词
应用型高校
财务管理专业
大数据课程
清晰集定性比较分析
课程设置
Application-oriented Universities
Financial Management Major
Big Data Courses
Qualitative Comparative Analysis
Course Curriculum
