所属学科门类:管理学
所属一级学科:工商管理
所属院系:统计与信息学院
一、培养目标
本专业旨在培养德才兼备,具有家国情怀和国际视野,具备良好政治素质与职业道德,具有现代管理学、经济学理论基础,掌握系统理论、信息管理、数据分析等知识,具有较高的信息技术应用能力,有较强的创新和实践能力,能够应用现代信息技术从事商务管理活动的高级复合型人才。
二、学制
本专业学制为2.5年。在规定时期完成课程学习,但未完成学位论文者,可申请延长学习年限,累计最长学习年限不超过4.5年。
三、研究方向
1.商务数据挖掘
2.智能信息系统
3.网络信息管理
四、课程设置与学分要求
本专业硕士研究生在攻读硕士学位期间应修满38学分,其中包括公共课7学分,学位基础课20学分,专业选修课6学分,跨专业选修课2学分,名师讲座2学分,社会实践1学分。此外,本专业硕士研究生必须通过国家英语六级考试,或者经相同水平的英语测试,达到合格要求。具体课程安排和学分见附表。
五、社会实践
根据本专业的培养方案,对于商务信息管理高级研究人才的培养,要求掌握高级数据库技术、管理学研究方法、运筹学、机器学习等学位基础课,掌握这些课程在科学研究中的应用能力。
对于商务信息管理应用型人才的培养,要求学生在研究生期间参加一定的社会实践。通过社会实践,培养学生的实践能力、分析问题和解决问题的能力以及综合运用所学基础知识和基本技能的能力,同时也为增强学生适应社会的能力和就业竞争力。社会实践内容的考核办法主要包括以下几个方面:(1)运用课堂学过的商务信息管理知识来分析和思考社会实践过程中发生的事情;(2)总结社会实践中的经验与教训,并将这些经验与教训总结成案例;(3)掌握与实习单位有关行业的基本知识与基本技能;(4)总结有关行业的管理知识与基本技能。成果是围绕上述内容写一篇社会实践报告。
具体要求见《必赢626net入口首页硕士研究生社会实践实施细则》。
六、科研能力
为了提高研究生学术科研能力,发挥研究生导师的指导作用,研究生在校期间必须在导师的指导下,从事科学研究,提高学术素养。
七、培养方式
商务信息管理专业的课程均采取讲授、讨论和专题研究的方式进行,对硕士研究生的培养实行导师负责制。
八、学位论文
研究生必须按规定时间完成学位论文撰写,经导师同意推荐答辩并通过校、院组织的论文盲审和答辩,论文质量达到所申请学位的合格要求。具体要求见《必赢626net入口首页硕士学位管理办法实施细则》。学位论文的写作要求见《必赢626net入口首页硕士学位论文内容和格式要求(2020年修订)》。
附表:
类别 | 课程名称 | 第1学期 | 第2学期 | 第3学期 | 学时 | 学分 | 开课部门 | |
公 共 课 | 中国特色社会主义理论与实践研究 | 2 |
|
| 36 | 2 | 马克思主义学院 | |
马克思主义与社会科学方法论研究 | 1 |
|
| 18 | 1 | 马克思主义学院 | ||
高级英语口语与写作 |
| 2 |
| 36 | 2 | 国际商务外语学院 | ||
商务信息管理前沿(英) |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
学 位 基 础 课 | 学术规范与论文写作 |
| 1 |
| 18 | 1 | 统计与信息学院 | |
管理学研究方法 | 2 |
|
| 36 | 2 | 工商管理学院 | ||
运筹学 | 3 |
|
| 54 | 3 | 统计与信息学院 | ||
高级程序设计 | 2 |
|
| 36 | 2 | 统计与信息学院 | ||
数据分析与统计建模 | 2 |
|
| 36 | 2 | 统计与信息学院 | ||
高级数据库技术 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
机器学习 |
| 3 |
| 54 | 3 | 统计与信息学院 | ||
神经网络与深度学习 |
|
| 2 | 36 | 2 | 统计与信息学院 | ||
管理决策理论与方法 |
| 3 |
| 54 | 3 | 统计与信息学院 | ||
选修课 | 专业选修 | 算法导论 |
| 2 |
| 36 | 2 | 统计与信息学院 |
复杂系统与复杂网络 |
|
| 2 | 36 | 2 | 统计与信息学院 | ||
高级计量经济学 | 3 |
|
| 54 | 3 | 统计与信息学院 | ||
时间序列分析 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
数据科学技术与应用 | 2 |
|
| 36 | 2 | 统计与信息学院 | ||
优化方法与数据分析实践 | 2 |
|
| 36 | 2 | 统计与信息学院 | ||
算法设计与实践 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
ERP理论与实践 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
文本挖掘技术 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
社会网络分析与计算方法 |
| 2 |
| 36 | 2 | 国际经贸学院 | ||
互联网前沿技术创新应用案例 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
计算机视觉 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
商务大数据案例分析 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
Android移动应用开发 |
| 2 |
| 36 | 2 | 统计与信息学院 | ||
跨专业
| 可拓学专题 |
| 2 |
| 36 | 2 | 统计与信息学院 | |
统计软件(R语言) |
|
| 2 | 36 | 2 | 统计与信息学院 | ||
心理与行为研究方法 |
|
| 2 | 36 | 2 | 工商管理学院 | ||
新媒体运营管理专题研究 |
|
| 2 | 36 | 2 | 工商管理学院 | ||
金融计量学 |
| 3 |
| 54 | 3 | 金融管理学院 | ||
电子商务 |
|
| 2 | 36 | 2 | 国际经贸学院 | ||
创业管理 |
|
| 2 | 36 | 2 | 工商管理学院 | ||
国际金融研究 |
|
| 2 | 36 | 2 | 金融管理学院 | ||
合同法 |
|
| 2 | 36 | 2 | 法学院 | ||
管理博弈论 |
| 2 |
| 36 | 2 | 工商管理学院 | ||
名师讲座 | 8次 | 2 | 统计与信息学院 | |||||
社会实践 |
| 1 | 统计与信息学院 |
MasterProgram in Business Information Management
for2022
Field:Management
Discipline:Business Administration
SchoolOffering the Program: School of Statistics and Information
I.Objectives
Thismajor aims to cultivate high-level composite talents with bothability and political integrity, have the feelings of home andcountry and international vision, have good political quality andprofessional ethics, have the theoretical foundation of modernmanagement and economics, master the knowledge of system theory,information management, data analysis, etc., have high informationtechnology application ability, have strong innovation and practicalability, and can apply modern information technology to engage inbusiness management activities.
Ⅱ.Duration of the Program
Theduration of this major is 2.5 years. Those who have completed thecourse within the prescribed period but have not completed thedissertation may apply for an extension of the study period, and thecumulative maximum study period shall not exceed 4.5 years.
Ⅲ.Research Areas
Business Data Mining
Intelligent Information System
Network Information Management
Ⅳ.Courses and Credits
Allstudents must earn 38 credits, including 7 “common required course”credits, 20 “required course” credits, 6 “major optionalcourse” credits, 2 “cross-specialty optional course” credits),2 “lecture course” credits and 1 “social practices” credit.In addition, master candidates in this program must pass CollegeEnglish Test (CET) 6 or an equivalent test of English languageproficiency to fulfil the requirement for graduation. Specific coursestructure can be found in the appendix.
Ⅴ.Social Practice
Accordingto the program plan, students who are going to be researchers arerequired to have a good knowledge of courses, such as AdvancedDatabase Technology, Methods in Management Research, OperationalResearch, Data Mining, Electronic Commerce and ERP Theory andPractice. They are also required to apply the learned knowledge inscientific research.
Forstudents who are going to be practical personnel, they are requiredto take part in social practice. Through social practice, we canequip students with practical abilities to analyze and solve problemsby using the basic knowledge and skills they learned in this program.Hence, we can enhance the social adaptability and employmentcompetitiveness. Social practice is to be assessed by the following:1) Analyze and consider the events occurring in the course of socialpractice by knowledge of business information management learned inclassroom. 2) Sum up the experiences and lessons in social practicefor case studies. 3) Command the basic knowledge and skill of theinternship and the relevant industry. 4) Summarize the managementknowledge and skills of the relevant industry. The outcome of socialpractice is a report covering the above points.
Forspecific requirements, please refer to the Detailed Rules for “theImplementation of social practice for master's degree students ofShanghai University of International Business and Economics”.
VI.Academic Training
Inorder to improve the academic research ability of graduate studentsand give full play to the research guidance role of graduate tutors,graduate students must engage in scientific research and improvetheir academic literacy under the guidance of their tutors.
VII.Education Modes
Thecourses of the business information management major are carried outin the form of lectures, discussions and special studies, and thetutor responsibility system is implemented for the training ofmaster's degree students.
VIII.Dissertation
Graduatestudents must complete the dissertation writing in accordance withthe prescribed time, and with the consent of the supervisor,recommend the defense and pass the thesis defense organized by theuniversity and the college, and the quality level of the thesis meetsthe qualified requirements of the applied degree. For specificrequirements, please refer to the “Detailed Rules for theImplementation of the Measures for the Administration of Master'sDegrees of Shanghai University of International Business andEconomics”. For the writing requirements of the dissertation,please refer to the “Content and Format Requirements for theMaster's Thesis of Shanghai University of International Business andEconomics (Revised in 2020)”.
AttachedTable:
Category | Course Name | Semester | Credit Hours | Credit | Department | |||
1 | 2 | 3 |
|
|
| |||
Common Required Courses | Socialist Theory and Practice with Chinese Characteristics | 2 |
|
| 36 | 2 | School of Marxism | |
Research on Marxism and Methodology of Social Science | 1 |
|
| 18 | 1 | School of Marxism | ||
Advanced Speaking and Writing |
| 2 |
| 36 | 2 | School of Languages | ||
Frontiers in Business Information Management |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Required Courses | Academic Standards and Paper Writing |
| 1 |
| 18 | 1 | School of Statistics and Information | |
Method of Management Research | 2 |
|
| 36 | 2 | School of Management | ||
Operational Research | 3 |
|
| 54 | 3 | School of Statistics and Information | ||
Advanced Programming | 2 |
|
| 36 | 2 | School of Statistics and Information | ||
Data Analysis and Statistical Modeling | 2 |
|
| 36 | 2 | School of Statistics and Information | ||
Advanced Database Technology |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Machine Learning |
| 3 |
| 54 | 3 | School of Statistics and Information | ||
Neural Network and Deep Learning |
|
| 2 | 36 | 2 | School of Statistics and Information | ||
Management Decision Theory and Method |
| 3 |
| 54 | 3 | School of Statistics and Information | ||
Optional Courses | Major Optional Courses | Algorithms Introduction |
| 2 |
| 36 | 2 | School of Statistics and Information |
The Design and Practice of Algorithm |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Complex System and Networks |
|
| 2 | 36 | 2 | School of Statistics and Information | ||
Advanced Econometrics | 3 |
|
| 54 | 3 | School of Statistics and Information | ||
Time Series Analysis |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Data Science Technology and Application | 2 |
|
| 36 | 2 | School of Statistics and Information | ||
Optimization Method and Data Analysis Practice | 2 |
|
| 36 | 2 | School of Statistics and Information | ||
ERP Theory and Practice |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Text Mining Technology |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Social Network Analysis and Calculation Methods |
| 2 |
| 36 | 2 | School of Business | ||
Internet Leading Technology Innovative Applications |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Computer Vision |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Business Big Data Case Analysis |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Android Mobile Application Development |
| 2 |
| 36 | 2 | School of Statistics and Information | ||
Cross Specialty Courses | Specific Lectures of Extenics |
| 2 |
| 36 | 2 | School of Statistics and Information | |
Statistical Software (R) |
|
| 2 | 36 | 2 | School of Statistics and Information | ||
Empirical Methods in Psychology and Behavior Research |
|
| 2 | 36 | 2 | School of Management | ||
New Media Operations Management |
|
| 2 | 36 | 2 | School of Management | ||
Financial Econometrics |
| 3 |
| 54 | 3 | School of Finance | ||
Electronic Commerce |
|
| 2 | 36 | 2 | School of Business | ||
Entrepreneurial Management |
|
| 2 | 36 | 2 | School of Management | ||
Research in International Finance |
|
| 2 | 36 | 2 | School of Finance | ||
Contract Law |
|
| 2 | 36 | 2 | School of Law | ||
Game Theory of Management |
| 2 |
| 36 | 2 | School of Management | ||
Lectures | 8 times | 2 | School of Statistics and Information | |||||
Social Practice |
| 1 | School of Statistics and Information |