MSc Thesis Defense Announcement of Ala' Alqaisi:"Trustworthy Decentralized Last Mile Delivery Framework Using Blockchain"

Monday, January 23, 2023 - 12:00 to 13:30

SCHOOL OF COMPUTER SCIENCE 

The School of Computer Science is pleased to present… 

MSc Thesis Defense by: Ala’ Alqaisi 

 
Date: Monday January 23, 2023 
Time:  12:00pm – 1:30pm 
Location: Essex Hall, Room 122 
Reminder: If you attend, it is mandatory that attendance is logged in both the sign-in sheet and  QR Code.
 

Abstract:  

The fierce competition and rapidly growing eCommerce market are painful headaches for logistics companies. In 2021, Canada Post’s parcel volume peaked at 361 million units with a minimum charge of $10 per each. The Last-Mile Delivery (LMD) is 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 on service levels and precise time windows. Therefore, it is the most complex and costly logistics process, accounting for more than 50% of the overall supply chain cost. Innovations like Crowdshipping, such as Uber Eats 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 rising. Besides, they lack transparency, and most of them, if not all, are platform monopolies in the making. 
New technologies such as blockchain recently introduced an opportunity to improve logistics and LMD operations. Several papers in the literature suggested employing blockchain and other cryptographic techniques for parcel delivery. Hence, this thesis presents a blockchain-based free-intermediaries crowd-logistics model and investigates the challenges that could harbor adopting this solution, such as user trust, data safety, security of transactions, and tracking service quality. Our framework combines a security assessment that examines the possible vulnerabilities of the proposed design and suggestions for mitigation and protection. Besides, it encourages couriers to act honestly by using a decentralized reputation model for couriers’ ratings based on their past behavior. 
 
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 
Chair: Dr Shafaq Khan     
 

 MSc Thesis Defense Announcement 

 

5113 Lambton Tower 401 Sunset Ave. Windsor ON, N9B 3P4 (519) 253-3000 Ext. 3716 csgradinfo@uwindsor.ca