Three Essays on Irregular Entries to the End-Customer Market

I study irregular entries to the end-customer market and the impact of such entries on suppliers, buyers, and customers. I am particularly interested in the irregularities of supplier encroachment and counterfeiting problems. This dissertation addresses these issues and proposes solutions in the form of three essays. In the first essay, I study a supply chain, consisting of a supplier and a buyer where the supplier can encroach on the end-customer market and keeps private information on its own production capacity. The supplier can decide on its capacity allocation and the buyer can order strategically, hoarding the supply capacity, to remove the competition. I find that the supplier is worse off, and the buyer is better off, when the supplier keeps its capacity information private. Further, I demonstrate that the supplier may no longer encroach on the end-customer market when it has more capacity. The second and third essays are inspired by the counterfeiting problem on online e-commerce platforms. In the second essay, I develop an algorithm that analyzes customers’ reviews on an online platform and provides an authenticity score for the products. I trained context-specific word embedding based on a large corpus of Amazon customer reviews to show that my unsupervised methodology provides good predictive power. Next, I study the effect of customers’ reviews on an e-commerce platform’s anti-counterfeiting strategy against third-party sellers. The platform can provide a tool for customers that analyzes just the product reviews or a more advanced tool that analyzes both the product and seller reviews to help customers determine if products are fake or genuine. On the seller’s side, it can choose to reveal its fake products by charging a lower separating price based on its profit under these two options. I demonstrate that even when the tools are free, the platform does not provide the advanced tool if the seller sells products with a low authenticity score (fake products), and it provides the basic tool if and only if the demand of the genuine product is sufficiently high. Together, these papers provide solutions on how to maximize profits by making informed decisions in the face of market irregularities for the supplier, the buyer, and the customer.

Name thesis:degree_name

Ph D

Discipline thesis:degree_discipline

Business

Grantor dc:publisher

The University of Western Ontario

Year dc:date.issued

2022

Author dc:creator

• Elahi, Hamid

Advisors dc:contributor.advisor

• Pun, H.
• Ghamat, S.

• Strategic Supply Chain Management
• Game Theory
• Counterfeit Detection
• Fuzzy c-Means
• Natural Language Processing.

Language dc:language.iso

en_ca

Handle dc:identifier.uri

https://hdl.handle.net/20.500.14721/32251

OAI identifier oai:identifier

oai:uwo.scholaris.ca:20.500.14721/32251