The 2018 MSOM Data Driven Research Challenge
Cainiao (Alibaba's logistics arm) and the MSOM society are partnering to offer MSOM members access to Cainiao's Transaction level data to encourage them to conduct data driven research.
In this competition, researchers will compete by building econometric models or data driven models using real data either to address some of the suggested questions below, or address questions of their own interest.
Eligibility Criteria: Who can enter?
(1) MSOM members as of INFORMS conference 2017 are encouraged to participate.
(2) At least one author of the submitted paper must be an MSOM member as of INFORMS conference 2018.
(3) Each MSOM member may enter the competition by submitting at most one paper.
Judging Criteria: What the judges will be looking for?
All entries will be judged according to the following criteria
Criteria 1: Data-Driven.
Criteria 2: Potential Impact on Practice.
Criteria 3: Contribution to the Research Literature.
Criteria 4: Generalizability / Scalability.
INFORMS 2017: Launch the competition.
September 1st, 2018: Competition submissions deadline.
October, 2018: Judges to review submissions and select finalists
October 20, 2018 during INFORMS conference (at Phoenix): Finalist presentations, judges select winners, and winner(s) announcement.
* Finalist will be invited for a Fast Track submission to M&SOM. Fast Track means that the paper will go through 1 round of review before making a final decision.
Data Acquisition and Submission Guidelines:
(1) The data hosting website is here.
(2) You need to be an MSOM member as of November 1st, 2017.
(3) Your MSOM registered email receives an email from Alibaba with an invitation code on November 10th, 2017. You are obliged not to share the code with non-MSOM members.
(4) With the invitation code, you need to follow this guideline to register a Tianchi account and download the data. (You can also download the guideline document here)
(5) Before the deadline, you can submit the paper to email@example.com.
* If you have any further questions, please email us at firstname.lastname@example.org with a title starting as "[Question]".
The committee and Cainiao find the following questions to be interesting. Researchers are welcome to explore these questions, variations of them, or other potentially relevant questions.
- How does the current reputation system impact consumer purchasing behavior? How could the platform change the design of the reputation system to improve a given platform-wide objective (e.g., consumer satisfaction, Gross Transaction Value)?
- Are there behavioral biases present in the reputation system of the platform? How could the platform re-design the reputation system to alleviate these biases and obtain information from reviews closer to the true operational performances?
- What are the frictions that the different services offered by Cainiao alleviate? Is it possible to quantify the economic value provided by them? Are there concrete recommendations that the platform could implement to enhance this value?
- Sellers and buyers interact through the Alibaba and Cainiao platforms. Are there synergies that could be exploited between the two? How can Alibaba use Cainiao effectively to enhance its value proposition and its profits?
- Can Cainiao’s platform be used to develop more accurate demand forecasts?
- What is the optimal inventory allocation across products and warehouses?
- How to optimize the distribution network to achieve the best trade-off between cost efficiency and fast delivery?
- How to monitor and incentivize third-party logistics firms to provide speedy service?
Cainiao Team Bio:
- Yinghui Xu
- Lijun Zhu
- Jiang Yang
- Yumin Deng