The PhD Summer Academy for PhD students is a 2 weeks intense period of learning for PhD students, debating, and discovering the fundamental concepts and recent trends in supply chain management, in addition to meeting future colleagues and having a great time in Zaragoza, Spain. ZLC is looking forward to receiving new applications for the Summer Academy 2021. Apply Now!
PhD Summer Academy 2021 Professors:
Dolores Romero Morales
Copenhagen Business School
Machine Learning / Data Driven Decision Making
Marshall School of Business, University of Southern California
Competition and Cooperation in Supply Chain
Robert H. Smith School of Business, University of Maryland
Online Market Design
College of Engineering, Northeastern University
Humanitarian and Emergency Response Logistics
Professors from past editions of the PhD Summer Academy added the following:
"The MIT-ZLC PhD Summer Academy program gave me the tools and skills to better tackle down my PhD studies. This program has given me the opportunity to enrich my academic and work experience with the interaction of peers in the Supply Chain Management from different parts of the world, the lecturers from respected professors in their field, and the opportunity of living in Zaragoza, the MIT experience has been a dream that certainly exceeded my expectations. I do recommend this program to supply chain Ph.D. candidates, as it will allow them to improve their expertise in research and expand their networking"
Lineth Rodríguez, Panama
PhD Candidate at Ecole Centrale Nantes
2021 Program Description
Course Description: Data Science aims to develop models that extract knowledge from complex data and represent it to aid Data Driven Decision Making. Data Science models should strike a balance between accuracy and interpretability. Interpretability is desirable, for instance, in medical diagnosis; it is required by regulators for models aiding, for instance, credit scoring; and since 2018 the EU extends this requirement by imposing the so-called right-to-explanation in algorithmic decision making. In this course, we first show that Mathematical Optimization is the natural tool to model the trade-off between accuracy and interpretability. Second, we show the latest advances on how to improve the accuracy of the popular classification and regression trees, seen as leaders in interpretability, and how to enhance the interpretability of black-box methods such as support vector machines. Finally, we illustrate an innovative data driven approach to model specification in regulatory benchmarking.
Course Description: There are many instances in different business areas where firms compete in their primary markets, while they still cooperate in some of their activities to achieve economies of scale and/or scope. For instance, independent retailers can jointly place their orders to reduce their fixed ordering costs; manufacturers can jointly organize recycling of their products if EPR legislations are implemented; etc. This type of problems can be studied by combining elements from non-cooperative and cooperative game theory. While cooperation among supply chain members should improve the overall performance of a supply chain, individual goals can induce one or more parties to make decisions that negatively impact the 9 performance of the system as a whole. In cooperative settings, overall performance is usually maximized when all parties act together (that is, form the grand coalition). However, some methods for allocation of profits/costs among collaborating parties can lead to situations in which individuals or groups can benefit by defecting and acting on their own, hence coalition stability is an important question in cooperative game theory. Stability of collaborative alliances is most commonly analyzed through the concept of the core. The core consists of allocation rules that yield a stable grand coalition (alliance of all players), as no set of players have an immediate incentive to defect from the grand coalition when gains are apportioned according to a core allocation. At the same time, the core suffers from myopia: it precludes the possibility that players and coalitions may consider the option that once they act (say, by forming a coalition), another coalition may react, and a third coalition might in turn react, and so on. It is not uncommon to observe defections and regrouping in markets before some stability is attained. One of the interesting features of dynamic stability is that it can identify stable structures even when static concepts conclude that there can be no stable outcomes. On the other hand, dynamic analysis can rule out the grand coalition as a candidate for stability even if the game has a nonempty core. When we forgo static concepts and assume a more realistic setting, in which the players consider possible consequences of their actions, we can obtain dramatically different results as to what are the likely stable structures, which can help companies in determining their operational strategies and in deciding whether to join an alliance or not. In this course, we will cover the concepts from non-cooperative and cooperative game theory with application to problems in operations management. The readings will draw from peer-reviewed articles in the operations management literature.
Course Description: The emergence of Internet-enabled platforms, such as Airbnb and Lyft, has highlighted that online marketplaces greatly reduce frictions that previously prevented buyers and sellers from connecting, thereby increasing the volume of trade in a number of markets. Typically, such platforms neither own nor directly control the goods involved in each transaction, but act as intermediaries. Thus, their success relies heavily on the design features of their respective marketplaces, e.g., the ways in which they organize and present information to the buyers and the timing with which they match and clear (portions of) the market. Online platforms connect an increasing number of sellers to deeper pools of potential buyers, be they consumer or business, both domestic and foreign. The opportunity for online intermediaries to create value has manifested itself not only in the cases exemplified by Airbnb and Lyft, but has also reshaped retail operations, particularly with regard to the handling and resale of liquidation inventory. The amount of inventory sold in these online platforms is highly variable. The uncertainty in supply coupled with the uncertain valuation of potential buyers, implies that online platforms face a familiar operational challenge: how to tailor their design so as to profitably match supply with demand. In this seminar, we will cover a range of papers that address online market design at a general level and then the specific challenges that face online B2B liquidation auctions. Papers will approach the problem of market design from a variety of methodological perspectives, including behavioral, empirical and optimization.
Course Description: Meeting demand in a timely and cost-effective manner is important both in public and private supply chains, and heavily depend on the design and operation of these supply chains. Demand is affected by ongoing factors such as local economy, infrastructure, and geographic location, as well as unexpected events such as natural or manmade disasters or other large-scale disruptions. Designing and operating responsive supply chains requires the consideration of uncertainty in timing, scope, scale, and understanding of various topics such as distribution network design and the role of human behavior. This course will examine methods and models for making supply chain design and operational decisions and explore the significant value that is obtained through informed decision-making in advance of an unpredictable event or long-term strategy for meeting the need of customers and beneficiaries.
In addition to being introduced to different topics in the field by a group of distinguished professors, it is a great opportunity to meet doctoral students from different institutions and exchange ideas. Although we expect applicants to come from different institutions, countries and backgrounds, the one common denominator is excellence. Applicants are selected to be part of a discussion forum made up of outstanding scholars in the area of logistics and supply chain management.
The PhD Summer Academy program is administered under the MIT-Zaragoza International Logistics Program, one of the select MIT educational and research partnerships. Upon completion of all courses to which you have enrolled, you will be awarded a certificate stating that you have completed a PhD summer course under the MIT- Zaragoza Program.
Who should apply
Every summer, a group of selected students and scholars from different institutions, countries and backgrounds get together to participate in an intense period of learning, debating, and discovering the fundamental concepts and recent trends in supply chain management.
When to apply
The PhD Summer Academy 2021 will take place in Zaragoza (Spain) from June 21 till July 1, 2021*.
All applications and supporting materials must be submitted by April 19, 2021.
*Calendar subject to minor changes.
Ready to apply?
- Current resume including academic degree, a brief list of the related courses taken so far (in the field of OR/IE/OM/Statistics), areas of research interest, specialization or competence, dissertation: the title and short description of your thesis, relevant work experience
- One recommendation letter from people capable of judging applicant´s professional and/or academic promise (i.e., supervisor, professor)
- Statement of interest for applying for the PhD Summer Academy. Please explain your specific area of academic interest (research topic you want to work on), how your education has prepared you to be successful in this program, what do you hope to achieve in this program. The statement should be no longer than 500 words
PhD Summer Academy Team
Tuition and Fees
Fee per Module: 300 €
Tuition Fee (4 modules) : 975 €
Early bird registration (ends March 22): 875 €
Alumni PhD Summer Academy: 700 €
Two students coming from the same university: 780 €
It is necessary to pay 875€* as a non-refundable deposit (with the exception of major reasons i.e COVID outbreak) to reserve their space in the Summer Academy 2021 class. The deadline for enrollment deposit is April 19, 2021.
To make a payment via international bank transfer, please use the following bank account information:
Beneficiary: Fundación Zaragoza Logistics Center
Bank: Ibercaja Banco SAU
Address: Plaza Basilio Paraíso 2, 50.008 Zaragoza (Spain)
SWIFT (International Bank Code): CAZRES2Z
IBAN (International Bank Account Number): ES62 2085 5200 8503 3328 7410
Also, when payments are in EUROS and for amounts bellow 500 Euros, credit card payments may be made via secure website: https://www.zlc.edu.es/payments/pos/
If payments are in another currency different to EUROS or over 500 Euros, please use the following link: https://zlc.flywire.com
Participants will have to make their own arrangements for their accommodation, meals, visa and transportation and must provide evidence of health insurance coverage while in Spain. The organization will be happy to help applicants with the travel and paperwork requirements.
Do you require further information?
Please fill in the following form to send an info request. Our admissions team are happy to assist you and answer any queries you may have about our master’s programs or the application process.