Transform Retail with Your Research鈥擲ubmit Your Proposal!听
The Retail Innovation Lab (RIL) at 黑料不打烊 University鈥檚 Bensadoun School of Retail Management, in partnership with Alimentation Couche-Tard, is calling for research proposals for the Winter 2025 semester.
Prize
The winner will receive a $1,000 cash prize and up to two runners-up will receive a $500 cash prize each. The winner and runners-up may also have an opportunity to collaborate with RIL-affiliated professors to implement their research proposals.
How to participate
- Any Ph.D. students or faculty members currently enrolled at 黑料不打烊 University can participate.听
- Each person can submit up to one (1) proposal under the topic 鈥淲hat research would you like to conduct in the retail innovation lab?鈥澨�
- The proposal can be no longer than five pages, including tables, figures, appendices, and references, if applicable.听
- The document must be printable on 8.5 x 11-inch paper, must use 11-point Times New Roman font with one-inch margins on all four sides, and must be single-spaced.
- Entries must be submitted as a single document in PDF format by 23:59 on April 30th to:
bsrmril-comp.mgmt [at] mcgill.ca (subject: Research%20proposals) .
Evaluation criteria
The proposal will be evaluated primarily based on the novelty of the idea both from academic and industry perspectives, the feasibility to execute it, and have a practical impact.
Data & technologies available
Customer Transaction Data
- Contains time-stamped transaction records, detailing:
- Items purchased
- Quantities
- Prices
- Promotions applied
- Payment transaction details (e.g., mode of payment: credit card, cash, debit)
- Checkout mode (e.g., self-checkout, cashier checkout)
- Continuously updated dataset, reflecting real-time transactional activity.
Inventory Information
- Records end-of-day stock levels for all products available in the store.
- Helps track product availability, replenishment rates, and demand patterns.
- Continuously updated dataset, ensuring real-time inventory tracking.
Store Planogram
- Represents the physical layout of the store, including aisle arrangements, product placements, and checkout areas.
- Provides insights into how customers navigate the store relative to product placements.
Customer Journey
- Captures timestamped trajectory data as XYZ coordinates, representing customer movement within the store.
- Includes customer 3D skeleton coordinates recorded at 5 frames per second (fps).
- For self-checkout, the data includes the customer trajectory with their basket.
- Timeframe: A one-time snapshot covering 5 months in 2023-24.
Eye tracking
- Pupil-center corneal reflection (PCCR), fixations, and other eye movements.
- Head movements: acceleration, rotation, and magnetic field strength.
- Scene camera: video of the wearer鈥檚 surroundings.
- Recording unit: audio, eye tracking data, and scene camera video.
Important dates
The submission due date is April 30, 2025 and presentation invites/dates are TBD.
In partnership with
