2021年天津大学管理与经济学部线上研究生暑期学校报名通知

天津大学管理与经济学部

2021-06-18 16:53 浏览量: 2440

为促进高校优秀研究生之间的学术交流，充分利用研究生教育的优质资源，开拓优秀博士生学术视野，并提升其理论功底与写作技能，天津大学管理与经济学部将于2021年7月12日—7月24日举办线上全国研究生暑期学校活动。

时间：2021年7月12日—7月24日

地点：中国 · 天津

开课形式：网络远程

课程设置

本期暑期学校拟开设以下8门课程（周日不开课），具体授课平台信息将于开课前发布。

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招生对象

本届暑期学校将面向全国招收在读博士研究生，以及少量海外博士研究生和有志于攻读天津大学管理学博士学位的硕士研究生。

为了保证教学质量，研究生暑期学校将采取限额申报，感兴趣的同学请抓紧报名。

报名方式

研究生暑期学校即日起接受报名，报名截止时间为6月28日12:00。

请将《附件2：暑期学校报名表》及《附件3：暑期学校报名信息统计表》发送至come_gs@tju.edu.cn，报名文档及邮件命名为“暑期学校报名-姓名-所在学校”。录取情况将于7月5日前以电子邮件或电话形式通知被录取学员，未接到录取通知的同学皆视为未录取，不另行通知。

请点击阅读原文下载相关文档。

附件1：课程及授课师资简介

附件2：暑期学校报名表

附件3：报名信息统计表

提取码: 1895

其他说明

1. 暑期学校结束后，将对合格学员颁发天津大学管理与经济学部2021年研究生暑期学校结业证书。

2. 本次暑期学校免收学杂费、报名费。

3. 无特殊情况，学员须全程参加暑期学校活动，不得中途或提前离开。

4. 联系方式：

（1）办公电话：022-27402304

（2）邮箱: come_gs@tju.edu.cn

5. 暑期学校相关工作的解释权在天津大学管理与经济学部。

课程及授课师资简介

课程Ⅰ：

Course Title: Social Operations Management

Instructor:

Prof. MingHu

The Rotman School,

The University of Toronto

Instructor Bio: Ming Hu is the University of Toronto Distinguished Professor of Business Operations and Analytics and a professor of operations management at the Rotman School. He was named as one of Poets & Quants Best 40 Under 40 business school professors in 2018. His research has been featured in mainstream media, including the Financial Times. Most recently, his research has focused on operations management in the context of two-sided markets, sharing economy, social buying, crowdfunding, crowdsourcing, etc., to make full use of operational decisions to benefit society. He recently edited a Springer book titledSharing Economy: Making Supply Meet Demandon operations management in the age of the sharing economy. He is the recipient of Wickham Skinner Early-Career Research Accomplishments Award by the POM Society (2016) and the Best Operations Management Paper inManagement ScienceAward by INFORMS (2017). He currently serves as the editor-in-chief ofNaval Research Logistics, department editor ofService Science, associate editor ofOperations Research,Management Science, andManufacturing & Service Operations Management, and senior editor ofProduction and Operations Management. He is a former chair of the Revenue Management and Pricing Section at INFORMS.

Course Description:Social Operations Management (SOM) is an emerging research area that focuses on the interactions between social behaviors and operations management decisions with applications in two-sided markets, sharing economy, social buying, crowdfunding, and crowdsourcing, etc. SOM is analogous to social economics in economics, with SOM emphasizing the more detailed operational decisions in the way that operations management differs from economics. SOM has the following distinctions. First, SOM differs from behavioral operations management (BOM), as SOM focuses on behavior influenced by external social interactions while BOM focuses on internal, psychological behavior. Second, SOM focuses on how social interactions, which lead to collective social behavior, have an impact on firms' operational decisions, and more importantly, how operational decisions can influence the formation of collective social behavior. Lastly, SOM often focuses on alternative socially responsible objectives than single-minded profit maximization. In this short course, I will use my own research to illustrate the basics and motivate further research in this area.

课程Ⅱ：

课程名称: 数字化供应链与创新

授课教师：

赵先德教授

中欧国际工商学院

个人简介: 赵先德博士是中欧国际工商学院京东运营及供应链管理学教席教授, 中欧-普洛斯供应链与服务创新中心主任，中欧国际工商学院企业数字化转型课程联席课程主任。赵教授的学术职务还包括国际供应链与运营管理学会（ASCOM）创始人及名誉主席、信息与管理科学国际学会（IMS）创会主席、决策科学组织亚太协会（APDSI）前主席等。他也是《运营管理期刊》的副主编与特刊主编，《决策科学期刊》的副主编，《生产与运营管理期刊》的高级主编，以及《数据、信息与管理期刊》的主编。赵教授的研究领域包括运营管理和供应链管理。他的研究主要集中在供应链整合与创新、基于网络平台的服务及商业模式创新、供应链金融、数字化供应链、基于大数据的供应链及物流决策优化等。他已在《运营管理期刊》、《消费者研究期刊》、《生产与运营管理》、《欧洲运筹学期刊》和《国际生产研究期刊》等高水平学术期刊上发表了190余篇的学术论文，近五年他发表了五本重要专著。此外，连续多年入围爱思唯尔（Elsevier）出版集团“商业、管理和会计领域”中国高被引学者榜单（2014-2019），亦曾获得包括运营管理领域全球最顶级期刊《运营管理期刊》的Jack Meredith最佳论文奖（2015, 2018）、中欧国际工商学院卓越研究奖（2015, 2016, 2018）、第十二届“钟家庆运筹学奖”(2018)在内的十余项学术荣誉，并于2020年获得决策科学院（Decision Science Institute, DSI）授予的院士头衔。赵教授还撰写了很多聚焦中国企业的教学案例，这些案例被哈佛案例库、毅伟案例库、中国工商管理国际案例库等权威案例库收录。他还为一些企业提供培训和咨询服务，如京东、海尔、中粮集团、西安强生、大连港集团、平安银行、建设银行、招商银行、创捷供应链、国药集团、中国移动、中国电信、中外运敦豪国际航空快递有限公司、日本航空公司、京都念慈庵有限公司、葛兰素史克公司、港华燃气、嘉里建设有限公司、广州钢铁集团等。

课程简介: 本课程的定位是“实践+案例为主、理论+研究为辅”。赵教授将结合近年来为实践者授课的经验与学术研究的发现，帮助学生了解业界正在发生的众多供应链创新故事，以及如何从实践中归纳研究问题、开展实证研究希望通过本课程来拓展学生对供应链管理的认识、增强学生对供应链管理的兴趣，以及帮助学生梳理本领域的一些研究机会。本课程主要包含三个专题：

1. 数字化供应链金融创新

学生将了解现代供应链金融的基本概念与发展趋势、以及不同种类的供应链金融创新实践。本专题将结合海尔日日顺网络供应链金融、创捷供应链、布比科技、普洛斯金融等企业案例，讲解供应链金融中的主要角色与合作模式、基于核心企业与金融机构的供应链金融模式创新、基于产业互联网服务平台的供应链金融模式创新、数字化技术与大数据的作用、供应链金融服务创新的成功要素等话题。

2. 物流供应链中的大数据应用

本专题将带领学生了解现代物流的发展趋势，以及数字化技术与大数据分析在物流供应链中的应用。本专题将结合顺丰、京东物流、易流科技、G7、中储智运等企业案例，让学生了解疫情期间的数字化应急物流管理、智慧物流的各类应用场景、技术与数据驱动的新物流商业模式、物流供应链的大数据管理等话题。

3. 数字化供应链与商业模式创新

本专题将拓展学生对现代供应链管理的认识，以及供应链不同环节的数字化转型与商业模式创新。本专题将结合海尔卡奥斯、尚品宅配、京东智能供应链、多点、盒马等企业案例，为学生讲述供应链在中国的不同发展阶段、新发展格局下的供应链能力需求、数字化技术与上下游协同如何推动不同行业的供应链与商业模式创新、产业互联网与消费互联网融合的最新趋势等话题。

课程Ⅲ：

Course Title:Selected research methods in Management Science and Engineering

Instructor:

Prof. Ou Tang

Linköping University,Sweden

Instructor Bio:Ou Tang is Professor of Production Economics at Linköping University, where he obtained a PhD in 2000. He served as associate editor and editor in the International Journal of Production Economics since 2008, and he is the past-president of the International Society for Inventory Research. Ou Tang’s principal research interest is in the field of operations and supply chain management, more specifically it includes inventory modelling, manufacturing planning and control systems, closed loop supply chain management, sustainable supply chains，supply chain risk management, and China related operations management issues. He has published more than 100 scientific articles, including 70 in international journals such as the European Journal of Operational Research, Computers and Operations Research, Omega, International Journal of Production Economics, Production and Operations Management, and others.

Ou Tang has extensive industrial experience with his research projects. As the principle investigator, he has audited and analyzed production and logistics systems, and proposed improvement suggestions in about 50 companies such as Volvo, Scania, Toyota, Siemens, Hewlett-Packard, General Electric, Ericsson, Electrolux, IKEA，Sapa, SSAB, Stora Enso, Alfa lava, Atlas Copco, SKF, among others.

Course Description: This doctoral seminar series provide a brief overview of research methodology and discuss some selected modelling approaches in Management Science and Engineering. The research field of Management Science has a scope on all managerial aspects of enterprises such as strategy, entrepreneurship, innovation, information technology, and organizations as well as all functional areas of business for example accounting, finance, marketing, and operations. The research approach can be either normative or descriptive, or alternatively it can be either quantitative, qualitative or a combination of two. In this seminar series, the focus will be put on selected research articles related to the research methodology and modelling techniques in the relevant areas. On completion of this seminar series, students should have gained some in-depth knowledge of the subject.

DAY1: Introduction

Overview of management science and engineering

Overview of research methodology

DAY2: Analytical models

Basics, general concept, decision analysis, behavior operations, models for inventory and pricing, classification of the systems

System dynamics

DAY3: Description of the systems, modelling examples, applications in energy system study

DAY4: Optimisation and heuristics

Overview, modelling techniques, heuristics, simulation and optimisation, experimental design

课程Ⅳ:

Game Theory and its Applications Across Different Domains

Instructor:

Prof. Subodha Kumar

Fox School of Business,

Temple University

Instructor Bio:Subodha Kumar is the Paul R. Anderson Distinguished Chair Professor of Marketing and Supply Chain Management and the Founding Director of the Center for Business Analytics and Disruptive Technologies at Temple University’s Fox School of Business. He has secondary appointments in Information Systems and Statistical Science Departments. He also serves as the Ph.D. Concentration Advisor for Operations and Supply Chain Management. He is a board member for many organizations. He has been awarded a Changjiang Scholars Chair Professorship by the China’s Ministry of Education. He is also a Visiting Professor at the Indian School of Business (ISB). He has served on the faculty of University of Washington and Texas A&M University. He has been the keynote speaker and track/cluster chairs at leading conferences. He was elected to become a Production and Operations Management Society (POMS) Fellow in 2019. He has received numerous other research and teaching awards. He has published more than 150 papers in reputed journals and refereed conferences. He was ranked #1 worldwide for publishing in Information Systems Research. In addition, he has authored a book, book chapters, Harvard Business School cases, and Ivey Business School cases. He also holds a robotics patent. He is routinely cited in different media outlets including NBC, CBS, Fox, Business Week, and New York Post. He is the Deputy Editor of Production and Operations Management Journal and the Founding Executive Editor of Management and Business Review (MBR). He also serves on other editorial boards. He was the conference chair for POMS 2018 and DSI 2018, and has co-chaired several other conferences.

CourseDescription: The overall goal of this course is multi-fold. First, I will introduce the basics of game-theoretic models. Second, I want all the students to be able to apply these methods for different problems. First, they should be able to model the problem using these methods. Second, they should be able to solve the problem to get useful analytical insights. In summary, the goal is to ensure that you should be able to see the bigger picture when you work on a problem. After some introductory lectures, students will present the related papers. We will also cover the issues as coordination, contracts, integration, and information sharing.

课程Ⅴ:

Course Title: Data driven decision making in operations management

Instructor:

Prof. Max Shen

The University of Hong Kong & The University of California, Berkeley

Instructor Bio: Max Shen is currently Vice-President and Pro-Vice-Chancellor (Research) of the University of Hong Kong, Chancellor’s Professor and Chair of the Department of Industrial Engineering and Operations Research and Professor of the Department of Civil and Environmental Engineering at the University of California, Berkeley, USA. He is also a Center Director at the Tsinghua-Berkeley Institute in Shenzhen and Honorary Professor and Department Chair of Industrial Engineering at Tsinghua University, China.

Professor Shen obtained his PhD from Northwestern University, USA in 2000, started his academic career as Assistant Professor at the University of Florida in the same year, and joined UC Berkeley in 2004 where he rose through the academic ranks to his present position. PhD students supervised by him now hold positions in top universities in North America, Europe and China including MIT, Oxford, etc. as well as leading technological companies including Google, Facebook, Amazon etc.

Internationally recognized as a top scholar in his field, Professor Shen is a Fellow of the Institute for Operations Research and the Management Sciences (INFORMS), the President-Elect of the Production and Operations Management (POM) Society, and the past President of the Society of Locational Analysis of the INFORMS.

CourseDescription:

DAY1: We investigate a data-driven multi-period inventory replenishment problem with uncertain demand and vendor lead time (VLT), with accessibility to a large quantity of historical data. Different from the traditional two-step predict-then-optimize (PTO) solution framework, we propose a one-step end-to-end (E2E) framework that uses deep-learning models to output the suggested replenishment amount directly from input features without any intermediate step. The E2E model is trained to capture the behavior of the optimal dynamic programming solution under historical observations, without any prior assumptions on the distributions of the demand and the VLT. By conducting a series of thorough numerical experiments using real data from one of the leading e-commerce companies, we demonstrate the advantages of the proposed E2E model over conventional PTO frameworks. We also conduct a field experiment with JD.com and the results show that our new algorithm reduces holding cost, stockout cost, total inventory cost and turnover rate substantially compared to JD's current practice. For the supply-chain management industry, our E2E model shortens the decision process and provides an automatic inventory management solution with the possibility to generalize and scale. The concept of E2E, which uses the input information directly for the ultimate goal, can also be useful in practice for other supply-chain management circumstances.

DAY2:With climate change, the already serious problem of forest fires is clearly becoming increasingly troublesome. This is happening in vast forest areas as well as in the transitional zone between urban and rural areas, with grave consequences to the population living in or near forests.

Analytic tools have been developed to determine what resources need to be in place, such as airplanes, helicopters, crews, and equipment, to help suppress fire. Once a fire has started, simulation models of fire spread have been quite successful in predicting the direction of fire to support decisions on how to deploy such resources.

Less emphasis has been given to preventive Landscape Design or Fuel Management, which leads to decisions on how to manage forests to minimize the impact of fires once they start. These decisions include harvesting, prescribed burnings, and others. This talk will present the different tools we have developed in this problem area. Our main effort is on the integration of prediction analysis of fire ignition and spread, and the decisions on landscape design. The techniques used include stochastic simulation, derivative-free optimization, machine learning, optimization, heuristics, and deep learning.

We have applied these techniques in a preliminary way in Chile, Spain, and Canada with the aim of translating research efforts into practical applications.

课程Ⅵ：

课程名称：超越高级实证研究

授课教师:

霍宝锋教授

天津大学管理与经济学部

个人简介: 霍宝锋博士是天津大学管理与经济学部主任、天津大学讲席教授、博士生导师、国家杰出青年基金获得者，Elsevier中国高被引学者。天津市社科联副主席、全国工商管理专业学位研究生教育指导委员会委员、天津市管理学科评议召集人。拥有香港中文大学运营管理专业的哲学博士学位、天津大学管理科学与工程专业的工学硕士和管理信息系统专业的工学学士学位。研究与教学领域包括运营管理、物流与供应链管理。论文发表在Journal of Operations Management, Production and Operations Management, Journal of Supply Chain Management, International Journal of Operations and Production Management, Journal of Business Logistics, IEEE Transactions on Engineering Management, International Journal of Production Research, International Journal of Production Economics, Information & Management, Business Horizons，《管理科学学报》、《系统工程理论与实践》、《科研管理》等期刊。担任《天津大学学报(社会科学版)》主编、Journal of Operations Management副主编、International Journal of Physical Distribution & Logistics Management高级副主编、Production and Operations Management编委、IEEE Transactions on Engineering Management编委, International Journal of Operations & Production Management编委，International Journal of Production Economics 编委, Industrial Management & Data Systems编委。在加入天津大学之前，曾先后担任西安交通大学管理学院助理教授、副教授和浙江大学管理学院教授、文科领军人才、求是特聘教授等工作。

课程简介:

第一讲：概念

什么是概念？概念的作用是什么？如何提出一个好的概念？如何操作化概念？概念与结构变量、观测变量的关系是什么？如何通过概念做学术贡献？如何通过概念的外衣认识真实事物？概念是艺术品吗？

第二讲：模型

什么是模型？模型的作用是什么？如何提出一个好的模型？好的模型，美的模型，完整的模型之间是什么关系？完美的模型存在吗？如果有完美的模型，应该是什么样子的？模型的美学意义是什么？

第三讲：数据

数据从哪里来？如何清洗数据？如何使用数据？数据分析里面的坑到底有多少？有多深？如何不为小数的位数烦恼？数据分析的哲学意义是什么？

第四讲：故事

会讲故事的人将拥有一切!

课程VII：

课程名称：创新管理：国际研究趋势和中国企业的实践

授课教师：

陈劲教授

清华大学经济管理学院

个人简介:陈劲，清华大学经济管理学院教授、博士生导师，教育部人文社会科学重点研究基地——清华大学技术创新研究中心主任，清华大学政策研究室特约研究员。学术期刊《International Journal of Innovation Studies》创始主编，《管理工程学报》《科学学与科学技术管理》副主编，以及《清华管理评论》执行主编等。陈劲教授于2000年获国务院政府特殊津贴，2002年荣获国家杰出青年基金，2007年获聘浙江大学“求是特聘教授”，2009年入选“国家百千万人才工程”，2014年获聘“长江学者特聘教授”。先后承担国家自然科学基金、国家社会科学基金、国家科技支撑计划项目等国家级课题10项，省部级课题30余项，获得省部级成果奖13项.陈劲教授在30年的学术研究过程中，着力研究具有中国特色的技术创新理论与应用体系，是整合式创新、有意义的创新等创新范式的提出者，是全面创新管理的核心研究者之一，是国内最先开展自主创新、开放式创新、协同创新研究的学者之一，也是“基于核心能力的企业创新生态系统”理论的提出者。截至2020年，陈劲在国内外学术期刊及会议上发表论文700余篇，其中多篇文章发表于《Research Policy》《Technovation》和《IEEE Transactions on Engineering Management》《Journal of Business Research》等工商管理主要英文期刊；出版专译著及编著100多部，其中，17部著作的影响力在一级学科排名前1%；先后在《人民日报》《光明日报》《科技日报》《瞭望》等发表多篇创新战略和政策的文章。

课程简介:本讲座系统介绍国际创新研究的若干趋势，如开放创新、用户创新和朴素式创新等，并进一步介绍整合式创新、有意义的创新、数字驱动的创新等新型创新范式，并进一步介绍创新管理的体系，以及中国优秀创新企业的最佳实践。

课程VIII：

Course Title: Data Driven Revenue Management

（JointOrganized withSchool of Management, The University of Science and Technology of China）

Instructor:

Prof.Chung Piaw TEO

The National University of Singapore

Instructor Bio: Chung Piaw TEO is Provost’s Chair Professor and Executive Director of the Institute of Operations Research and Analytics (IORA) in the National University of Singapore. Prior to the current appointments, he was a Head of Department, Acting Deputy Dean, Vice-Dean of the Research and Ph.D Program as well as Chair of the Ph.D Committee in the NUS Business School.

He was a fellow in the Singapore-MIT Alliance Program, an Eschbach Scholar in Northwestern University (US), Professor in Sungkyunkwan Graduate School of Business (Korea), and a Distinguished Visiting Professor in YuanZe University (Taiwan). He is an elected Fellow in INFORMS and a Chang Jiang Scholar with USTC.

He studied issues in service and manufacturing operations, supply chain management, discrete optimization, and machine learning. He is currently spearheading an effort to develop the Institute of Operations Research and Analytics, as part of NUS strategic initiatives in the Smart Nation Research Program.

He is a department editor for MS (Optimization), and a former area editor for OR (Operations and Supply Chains). He has also served on several international committees such as the Chair of the Nicholson Paper Competition (INFORMS, US), member of the LANCHESTER and IMPACT Prize Committee (INFORMS, US), Fudan Prize Committee on Outstanding Contribution to Management (China).

CourseDescription:Revenue management emerged in the US airline industry after the deregulation in the 1980s. It has been successfully implemented by companies in air transportation, hospitality (hotels, cruises, theme parks, casinos), car rental, media, broadcasting, natural-gas storage and transmission, electricity generation and transmission, show business (concerts, theaters, sports events), universities. Most applications are recent and made possible by the advances in technology, information systems, and data mining. This short course introduces recent advances in the theory and practice of modern revenue management and dynamic pricing. The topics discussed include online revenue management, dynamic choice behaviors, and representative consumer choice model. We will show how theories can be integrated with data to obtain useful insights into the problem.

心动不如行动

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