MSc Thesis Proposal Announcement by Ala' Alqaisi:"Decentralized Last Mile Delivery using Crowdshipping and Blockchain"

Wednesday, December 1, 2021 - 10:00 to 11:30


The School of Computer Science is pleased to present… 

MSc Thesis Proposal by: Ala’ Alqaisi 

Date: Wednesday December 1st, 2021 
Time:  10:00am - 11:30am 
Passcode: If interested in attending this event, contact the Graduate Secretary at with sufficient notice before the event to obtain the passcode.


The fierce competition and enormous growth in the eCommerce market are a painful headache for logistics companies. In 2020, Canada Post delivered around 389 million parcels with a minimum charge of $10 per each. When you receive an "Out for delivery" notification, this step is called Last-Mile Delivery (LMD), the final leg of the supply chain that ends with the package at the customer's doorstep. LMD involves moving small shipments to geographically dispersed locations with high expectations of service levels and precise time windows. Therefore, it is the most complex and costly part of the logistics process, accounting for more than 50% of the overall supply chain cost. Innovations like Crowdshipping, such as Uber and Amazon Flex, help overcome this inefficiency and provide an outstanding delivery experience by enabling freelancers willing to deliver packages if they are around. However, apart from the centralized nature of the Crowdshipping platforms, retailers pay a fee for outsourcing the delivery process, which is on the rise. So, what if we can eliminate the need for these apps and connect you and the community with a crowd of couriers directly? Would you trust such an alternative? 
Recently cryptocurrencies have given the means to buy and sell items in a decentralized manner. Hence, this research investigates methods and techniques to utilize Crowdshipping and Blockchain to design a P2P decentralized LMD platform. Our objective is to eliminate the need for a mediator or a third party without compromising the security and trust of the proposed platform. We will leverage modern and reliable reputation system design principles and threat modelling mechanisms to identify potential threats and employ the relevant security protocols and design patterns. 
Keywords: Last Mile Delivery, Crowdshipping, Blockchain, Threat Modelling, Reputation 

MSc Thesis Committee:

Internal Reader: Dr Xiaobu Yuan
External Reader: Dr Fazle Baki
Advisor: Dr Sherif Saad

MSc Thesis Proposal Announcement 

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