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Ontario Tech acknowledges the lands and people of the Mississaugas of Scugog Island First Nation.

We are thankful to be welcome on these lands in friendship. The lands we are situated on are covered by the Williams Treaties and are the traditional territory of the Mississaugas, a branch of the greater Anishinaabeg Nation, including Algonquin, Ojibway, Odawa and Pottawatomi. These lands remain home to many Indigenous nations and peoples.

We acknowledge this land out of respect for the Indigenous nations who have cared for Turtle Island, also called North America, from before the arrival of settler peoples until this day. Most importantly, we acknowledge that the history of these lands has been tainted by poor treatment and a lack of friendship with the First Nations who call them home.

This history is something we are all affected by because we are all treaty people in Canada. We all have a shared history to reflect on, and each of us is affected by this history in different ways. Our past defines our present, but if we move forward as friends and allies, then it does not have to define our future.

Learn more about Indigenous Education and Cultural Services

March 16, 2012

Speaker: Professor Chi-Guhn Lee, Department of Mechanical and Industrial Engineering, University of Toronto

Title: A micro-diffusion model for innovative products with herding

Abstract: Throughout history there have been many examples of innovations that for-some-reason were incredibly successful. On the other hand, there are also numerous examples of innovations that may be deemed as incredible failures. New products are an important source of sales and profit for a firm; furthermore, new product developments typically involve large financial commitments. As a result, forecasting the acceptance of a new product, and marketing the product correctly while keeping in mind market conditions would be a significant advantage to any firm. However, this task can often be difficult. We present a word of mouth diffusion model that aims to shed some light on these conditions, and provide a tool to aid in the planning of the launch of a new innovation. It is able to capture the process by which customers become aware of a new technology via a diffusion function, and the adoption decision at the micro-level.

Biography: Professor Lee is an associate professor in the Department of Mechanical and Industrial Engineering at the University of Toronto. He received a PhD in the area of Operations and Industrial Engineering from the University of Michigan, Ann Arbor, in 2001 and join at the University of Toronto in the same year. His expertise covers a wide range of optimization theories such as stochastic modelling, statistical analysis, mathematical programming, stochastic programming, and theory of sequential decision making under uncertainty. The list of applications that he has addressed in the recent past involves inventory management, transportation planning and scheduling, facility location problems, supply chain management and procurement optimization, valuation of contingent claims, healthcare optimization and dynamic pricing and revenue management.