Document Type


Degree Name

Doctor of Philosophy (PhD)



Program Name/Specialization

Operations and Supply Chain Management


Lazaridis School of Business and Economics

First Advisor

Mojtaba Araghi

Advisor Role

Associate Professor


This dissertation investigates three profit maximization models for coordinating Sales and Operations (S\&OP) management.

The first problem considers implementing a customer education strategy for the digital channel users of a multi-channel service provider. Using a customer network flow model, I investigate the effect of customer education in the digital channel on the number of users of digital and in-person channels. Further, I define a customer value metric that characterizes the optimal level of education effort. Finally, I determine conditions under which the effect of positive word-of-mouth regarding the quality of education dominates the lifetime value of customers.

The second problem studies a supply chain in which a distributor procures perishable products, transports them along the supply chain through distribution centers, and sells them at retail stores. The objective is to jointly optimize quality-based transportation decisions and pricing policies. I propose two frameworks to study this problem under sequential and integrated systems. Pricing and transportation decisions are made separately and then coordinated through an iterative process in the sequential model but jointly optimized in the integrated system.

I exploit the special structure of the integrated model formulation and develop a decomposition-based solution method. I tested the model and solution methodology on a lettuce product distribution network in Eastern Canada.

Finally, the third problem investigates the category space allocation at the macro-level and explores how considering location-based and product-based attractiveness can improve a retailer's overall space profitability. I consider both location-based and product-based attractiveness factors in a mixed-integer quadratic problem. As large-scale instances of this problem are computationally challenging to solve, I further provide a decomposition-based heuristic solution method for solving large instances of the problem.

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